290 Research Engineer jobs in India

Research Engineer, Applied Research (Biotech AI – Drug Discovery)

About the Company

Quantiphi is an award-winning AI-first digital engineering company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Quantiphi has seen 2.5x growth YoY since its inception in 2013 to 3500+ team members globally.

For more details, please visit our website or LinkedIn page.

About the Applied Research Unit

Applied Research is an R&D practice at Quantiphi focused on advancing the frontiers of AI technologies with Applied Machine Learning at its core. We ideate and build novel solutions to high-impact, cutting-edge challenges, with a focus on advanced prototyping and scalable proof of concepts.

Within this unit, the AI-Accelerated Drug Discovery practice is a key pillar that aims to apply state-of-the-art AI methodologies to revolutionize the way new therapeutics are discovered and developed. We are committed to driving meaningful scientific breakthroughs by combining strong AI research with deep cross-disciplinary collaboration.

Job Description

Role Level: Research Engineer

Work Location: India

Resource Count: 2

The Role

This is a unique opportunity to work on scientifically impactful problems at the intersection of AI and biotechnology within Quantiphi Applied Research team. In this role, you will work on the development of core AI models and algorithms aimed at accelerating the drug discovery process. The position focuses on advancing foundational AI techniques such as generative modeling, optimization, and reinforcement learning, applied to molecular and bio-pharmaceutical data.

The position involves working with a diverse, lively, and proactive group of nerds who are constantly raising the bar on translating the latest AI research in Healthcare and Life Sciences into tangible reusable assets for the community. Hence this would require a high level of conceptual understanding, attention to detail and agility in terms of adaptation to new technologies.

While prior experience in the biotech or life sciences domain is highly valued and will elevate the candidate profile, we are equally open to exceptional AI/ML researchers from other domains who are excited to explore and learn the nuances of this rapidly growing field .

Please note: This is a core AI research role, not a software engineering or system integration position. We are particularly keen to engage with candidates focused on scientific AI innovation rather than application development or LLM/GenAI-centric workflows .

Responsibilities

• Stay ahead of the AI research curve, focusing on foundational AI methodologies applicable to drug discovery and molecular design.
• Build rapid prototypes, conduct detailed experimental studies, and develop advanced AI models in areas such as generative modeling, reinforcement learning, graph-based learning, and molecular property prediction.
• Work closely with interdisciplinary teams including biologists, chemists, and life science domain experts to design scientifically sound AI approaches.
• Contribute to Quantiphi IP portfolio through the development of novel algorithms, proof of concepts, and potential publications.
• Drive thought leadership through documentation, knowledge dissemination, and participation in conferences, blogs, webinars, and publications.
• Publish Research papers in prestigious Conferences and Journals

Requirements

Must Have:

• Master’s degree, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields.
• Minimum work experience required : from new graduates to 3+ yrs of research experience post graduation (in ML research)
• Strong foundation in AI/ML concepts with hands-on experience in model development, experimental design, and large-scale data analysis.
• Excellent in-depth understanding of ML concepts and the respective underlying mathematical know-how.
• Working knowledge of using NLP with biological sequences.
• Solid research mindset with a track record of working on complex AI problems—experience with drug discovery datasets is a plus but not a prerequisite.
• Excellent programming skills in Python, with experience using AI/ML frameworks like PyTorch or TensorFlow.
• Hands-on experience in developing and deploying models with various deep learning architectures in multiple ML areas like Computer-Vision, NLP, Statistics etc
• Ability to independently learn new scientific domains and apply AI techniques to novel bio-pharmaceutical problems.
• Strong communication skills with the ability to present complex ideas in an accessible format across audiences.
• Ability to translate abstract highlights into understandable insights in multiple knowledge-dissemination formats like blogs, presentations, paper-publications, tutorials and webinars

Good to Have:

• Prior exposure to molecular datasets, cheminformatics, bioinformatics, or life sciences.
• Hands-on experience with insilico techniques in drug discovery
• Hands-on experience with HPC workflows with genome datasets
• Familiarity with generative chemistry models, graph neural networks, reinforcement learning, or multi-objective optimization.
• Demonstrated industry research experience will be considered as an additional bonus.
• Research publications in AI/ML conferences such as NeurIPS, ICML, ICLR, or relevant bioinformatics journals
• Experience with cloud environments like GCP or AWS and scalable model training.
• Strong classical education on math/physics/mechanics/CS/Engineering concepts will also be an advantage.

Why Join Us?

• Opportunity to work at the cutting edge of AI and biotechnology, solving problems with real-world scientific impact.
• Exposure to interdisciplinary teams and a culture that encourages continuous learning and exploration.
• Contribute to an R&D environment that values curiosity, innovation, and the advancement of AI for good.

Research Engineer, Applied Research (Biotech AI – Drug Discovery)

About the Company
Quantiphi is an award-winning AI-first digital engineering company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.
Quantiphi has seen 2.5x growth YoY since its inception in 2013 to 3500+ team members globally.
For more details, please visit our website or LinkedIn page.

About the Applied Research Unit
Applied Research is an R&D practice at Quantiphi focused on advancing the frontiers of AI technologies with Applied Machine Learning at its core. We ideate and build novel solutions to high-impact, cutting-edge challenges, with a focus on advanced prototyping and scalable proof of concepts.
Within this unit, the AI-Accelerated Drug Discovery practice is a key pillar that aims to apply state-of-the-art AI methodologies to revolutionize the way new therapeutics are discovered and developed. We are committed to driving meaningful scientific breakthroughs by combining strong AI research with deep cross-disciplinary collaboration.

Job Description
Role Level: Research Engineer
Work Location: India
Resource Count: 2

The Role
This is a unique opportunity to work on scientifically impactful problems at the intersection of AI and biotechnology within Quantiphi Applied Research team. In this role, you will work on the development of core AI models and algorithms aimed at accelerating the drug discovery process. The position focuses on advancing foundational AI techniques such as generative modeling, optimization, and reinforcement learning, applied to molecular and bio-pharmaceutical data.
The position involves working with a diverse, lively, and proactive group of nerds who are constantly raising the bar on translating the latest AI research in Healthcare and Life Sciences into tangible reusable assets for the community. Hence this would require a high level of conceptual understanding, attention to detail and agility in terms of adaptation to new technologies.
While prior experience in the biotech or life sciences domain is highly valued and will elevate the candidate profile, we are equally open to exceptional AI/ML researchers from other domains who are excited to explore and learn the nuances of this rapidly growing field .
Please note: This is a core AI research role, not a software engineering or system integration position. We are particularly keen to engage with candidates focused on scientific AI innovation rather than application development or LLM/GenAI-centric workflows .
Responsibilities
Stay ahead of the AI research curve, focusing on foundational AI methodologies applicable to drug discovery and molecular design.
Build rapid prototypes, conduct detailed experimental studies, and develop advanced AI models in areas such as generative modeling, reinforcement learning, graph-based learning, and molecular property prediction.
Work closely with interdisciplinary teams including biologists, chemists, and life science domain experts to design scientifically sound AI approaches.
Contribute to Quantiphi IP portfolio through the development of novel algorithms, proof of concepts, and potential publications.
Drive thought leadership through documentation, knowledge dissemination, and participation in conferences, blogs, webinars, and publications.
Publish Research papers in prestigious Conferences and Journals
Requirements
Must Have:
Master’s degree, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields.
Minimum work experience required : from new graduates to 3+ yrs of research experience post graduation (in ML research)
Strong foundation in AI/ML concepts with hands-on experience in model development, experimental design, and large-scale data analysis.
Excellent in-depth understanding of ML concepts and the respective underlying mathematical know-how.
Working knowledge of using NLP with biological sequences.
Solid research mindset with a track record of working on complex AI problems—experience with drug discovery datasets is a plus but not a prerequisite.
Excellent programming skills in Python, with experience using AI/ML frameworks like PyTorch or TensorFlow.
Hands-on experience in developing and deploying models with various deep learning architectures in multiple ML areas like Computer-Vision, NLP, Statistics etc
Ability to independently learn new scientific domains and apply AI techniques to novel bio-pharmaceutical problems.
Strong communication skills with the ability to present complex ideas in an accessible format across audiences.
Ability to translate abstract highlights into understandable insights in multiple knowledge-dissemination formats like blogs, presentations, paper-publications, tutorials and webinars
Good to Have:
Prior exposure to molecular datasets, cheminformatics, bioinformatics, or life sciences.
Hands-on experience with insilico techniques in drug discovery
Hands-on experience with HPC workflows with genome datasets
Familiarity with generative chemistry models, graph neural networks, reinforcement learning, or multi-objective optimization.
Demonstrated industry research experience will be considered as an additional bonus.
Research publications in AI/ML conferences such as NeurIPS, ICML, ICLR, or relevant bioinformatics journals
Experience with cloud environments like GCP or AWS and scalable model training.
Strong classical education on math/physics/mechanics/CS/Engineering concepts will also be an advantage.
Why Join Us?
Opportunity to work at the cutting edge of AI and biotechnology, solving problems with real-world scientific impact.
Exposure to interdisciplinary teams and a culture that encourages continuous learning and exploration.
Contribute to an R&D environment that values curiosity, innovation, and the advancement of AI for good.

Research Engineer, Applied Research (Biotech AI – Drug Discovery)

About the Company

Quantiphi is an award-winning AI-first digital engineering company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Quantiphi has seen 2.5x growth YoY since its inception in 2013 to 3500+ team members globally.

For more details, please visit our website or page.

About the Applied Research Unit

Applied Research is an R&D practice at Quantiphi focused on advancing the frontiers of AI technologies with Applied Machine Learning at its core. We ideate and build novel solutions to high-impact, cutting-edge challenges, with a focus on advanced prototyping and scalable proof of concepts.

Within this unit, the AI-Accelerated Drug Discovery practice is a key pillar that aims to apply state-of-the-art AI methodologies to revolutionize the way new therapeutics are discovered and developed. We are committed to driving meaningful scientific breakthroughs by combining strong AI research with deep cross-disciplinary collaboration.

Job Description

Role Level: Research Engineer

Work Location: India

Resource Count: 2

The Role

This is a unique opportunity to work on scientifically impactful problems at the intersection of AI and biotechnology within Quantiphi Applied Research team. In this role, you will work on the development of core AI models and algorithms aimed at accelerating the drug discovery process. The position focuses on advancing foundational AI techniques such as generative modeling, optimization, and reinforcement learning, applied to molecular and bio-pharmaceutical data.

The position involves working with a diverse, lively, and proactive group of nerds who are constantly raising the bar on translating the latest AI research in Healthcare and Life Sciences into tangible reusable assets for the community. Hence this would require a high level of conceptual understanding, attention to detail and agility in terms of adaptation to new technologies.

While prior experience in the biotech or life sciences domain is highly valued and will elevate the candidate profile, we are equally open to exceptional AI/ML researchers from other domains who are excited to explore and learn the nuances of this rapidly growing field .

Please note: This is a core AI research role, not a software engineering or system integration position. We are particularly keen to engage with candidates focused on scientific AI innovation rather than application development or LLM/GenAI-centric workflows .

Responsibilities

• Stay ahead of the AI research curve, focusing on foundational AI methodologies applicable to drug discovery and molecular design.
• Build rapid prototypes, conduct detailed experimental studies, and develop advanced AI models in areas such as generative modeling, reinforcement learning, graph-based learning, and molecular property prediction.
• Work closely with interdisciplinary teams including biologists, chemists, and life science domain experts to design scientifically sound AI approaches.
• Contribute to Quantiphi IP portfolio through the development of novel algorithms, proof of concepts, and potential publications.
• Drive thought leadership through documentation, knowledge dissemination, and participation in conferences, blogs, webinars, and publications.
• Publish Research papers in prestigious Conferences and Journals

Requirements

Must Have:

• Master’s degree, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields.
• Minimum work experience required : from new graduates to 3+ yrs of research experience post graduation (in ML research)
• Strong foundation in AI/ML concepts with hands-on experience in model development, experimental design, and large-scale data analysis.
• Excellent in-depth understanding of ML concepts and the respective underlying mathematical know-how.
• Working knowledge of using NLP with biological sequences.
• Solid research mindset with a track record of working on complex AI problems—experience with drug discovery datasets is a plus but not a prerequisite.
• Excellent programming skills in Python, with experience using AI/ML frameworks like PyTorch or TensorFlow.
• Hands-on experience in developing and deploying models with various deep learning architectures in multiple ML areas like Computer-Vision, NLP, Statistics etc
• Ability to independently learn new scientific domains and apply AI techniques to novel bio-pharmaceutical problems.
• Strong communication skills with the ability to present complex ideas in an accessible format across audiences.
• Ability to translate abstract highlights into understandable insights in multiple knowledge-dissemination formats like blogs, presentations, paper-publications, tutorials and webinars

Good to Have:

• Prior exposure to molecular datasets, cheminformatics, bioinformatics, or life sciences.
• Hands-on experience with insilico techniques in drug discovery
• Hands-on experience with HPC workflows with genome datasets
• Familiarity with generative chemistry models, graph neural networks, reinforcement learning, or multi-objective optimization.
• Demonstrated industry research experience will be considered as an additional bonus.
• Research publications in AI/ML conferences such as NeurIPS, ICML, ICLR, or relevant bioinformatics journals
• Experience with cloud environments like GCP or AWS and scalable model training.
• Strong classical education on math/physics/mechanics/CS/Engineering concepts will also be an advantage.

Why Join Us?

• Opportunity to work at the cutting edge of AI and biotechnology, solving problems with real-world scientific impact.
• Exposure to interdisciplinary teams and a culture that encourages continuous learning and exploration.
• Contribute to an R&D environment that values curiosity, innovation, and the advancement of AI for good.

About QpiAI

At QpiAI, we are leading the effort to discover optimal AI and Quantum systems in Life sciences,

Healthcare, Transportation, Finance, Industrial, and Space technologies. QpiAI is building a full-

stack Enterprise Quantum Computers.

QpiAI Quantum hardware team is responsible for designing and characterisation of Quantum

Processor, Cryogenic Quantum Control Circuits, RF Control Hardware, and QpiAI ASGP.

About the Role

We are building high-performance optimization infrastructure for real-world decision-making problems across logistics, manufacturing, and emerging tech domains. We are looking for a mathematically inclined, algorithmically sharp engineer who thrives at the intersection of theory and systems — someone who can translate abstract optimization problems into efficient, production-ready solvers.

Key Responsibilities

• Design and implement fast, scalable solvers for complex optimization problems across discrete and continuous domains.
• Develop constraint modeling frameworks and metaheuristic algorithms grounded in strong mathematical principles.
• Evaluate solution quality, convergence behavior, and performance benchmarks across diverse instances and datasets.
• Work with system engineers to integrate your solver modules into larger optimization stacks and real-time decision systems.
• Explore and adapt techniques from mathematical programming, stochastic methods, and quantum-inspired approaches.

What We're Looking For

• Strong foundation in mathematics : linear algebra, combinatorics, graph theory, numerical methods, convex and discrete optimization.
• Algorithmic and systems thinking : should be able to write fast, memory-efficient code and optimize for performance bottlenecks.
• Exceptional programming skills in Python and C++ (or Rust/Julia); low-level optimizations and profiler-driven development are a plus.
• Experience with algorithm design for constraint systems, heuristics, and metaheuristics.
• Hands-on coding profile : A high rating on platforms like Leetcode, Codeforces, or Hackerrank is a strong signal.
• Product thinking : capable of modular, reusable, and extensible solver design; understands how solvers scale in production systems.
• Exposure to quantum computing or hybrid quantum-classical paradigms is a plus.

Good to Have

• Familiarity with model encoding techniques and constraint representations.
• Benchmarking experience on large-scale combinatorial datasets.
• Participation in mathematical modeling competitions (e.g., INMO, COMAP, Kaggle competitions involving optimization).

Why Join Us

You’ll work closely with a team that understands optimization not just as a mathematical challenge, but as a product engineering problem. If you're excited about building fast solvers, pushing boundaries in hybrid or hardware-accelerated optimization, and solving problems at scale, we’d love to hear from you.

About QpiAI
At QpiAI, we are leading the effort to discover optimal AI and Quantum systems in Life sciences,
Healthcare, Transportation, Finance, Industrial, and Space technologies. QpiAI is building a full-
stack Enterprise Quantum Computers.
QpiAI Quantum hardware team is responsible for designing and characterisation of Quantum
Processor, Cryogenic Quantum Control Circuits, RF Control Hardware, and QpiAI ASGP.

About the Role
We are building high-performance optimization infrastructure for real-world decision-making problems across logistics, manufacturing, and emerging tech domains. We are looking for a mathematically inclined, algorithmically sharp engineer who thrives at the intersection of theory and systems — someone who can translate abstract optimization problems into efficient, production-ready solvers.

Key Responsibilities
Design and implement fast, scalable solvers for complex optimization problems across discrete and continuous domains.
Develop constraint modeling frameworks and metaheuristic algorithms grounded in strong mathematical principles.
Evaluate solution quality, convergence behavior, and performance benchmarks across diverse instances and datasets.
Work with system engineers to integrate your solver modules into larger optimization stacks and real-time decision systems.
Explore and adapt techniques from mathematical programming, stochastic methods, and quantum-inspired approaches.

What We're Looking For
Strong foundation in mathematics : linear algebra, combinatorics, graph theory, numerical methods, convex and discrete optimization.
Algorithmic and systems thinking : should be able to write fast, memory-efficient code and optimize for performance bottlenecks.
Exceptional programming skills in Python and C++ (or Rust/Julia); low-level optimizations and profiler-driven development are a plus.
Experience with algorithm design for constraint systems, heuristics, and metaheuristics.
Hands-on coding profile : A high rating on platforms like Leetcode, Codeforces, or Hackerrank is a strong signal.
Product thinking : capable of modular, reusable, and extensible solver design; understands how solvers scale in production systems.
Exposure to quantum computing or hybrid quantum-classical paradigms is a plus.

Good to Have
Familiarity with model encoding techniques and constraint representations.
Benchmarking experience on large-scale combinatorial datasets.
Participation in mathematical modeling competitions (e.g., INMO, COMAP, Kaggle competitions involving optimization).

Why Join Us
You’ll work closely with a team that understands optimization not just as a mathematical challenge, but as a product engineering problem. If you're excited about building fast solvers, pushing boundaries in hybrid or hardware-accelerated optimization, and solving problems at scale, we’d love to hear from you.

About us

At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.

The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies. 

We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we can work together .

What role you will play in our team

Operations Research Engineers function as internal consultants to support improved decision-making by developing models using operations research methods, such as mathematical optimization and stochastic simulation. They will work in a team environment to apply their technical skills, project management, and business domain knowledge to develop technological and analytics solutions in partnership with business units to influence and improve key business decisions.

The Operations Research Engineer is expected to work with global, cross-functional stakeholders to understand business problems (both commercially and technically),  translate them into mathematical problems, and apply operations research methods to create solutions for decision support. This role will primarily work on business problems related to supply chain and commercial functions, especially for Fuels, Lubes, and Chemical products.

What you will do

• Participate in the scoping of business problems to apply operations research methods
• Work with key contacts to identify and translate data requirements which represent the system and constraints to be modeled
• Develop custom mathematical optimization and/or stochastic simulation models by applying the following: linear programming, mixed-integer programming, system dynamics simulation, and/or discrete event simulation
• Proactively drive cross-functional alignment across organizations (as needed) to validate model solution quality
• Create documentation to explain how the operations research methods are applied, and conduct reviews with senior technical professionals to ensure technical quality
• Ensure effective and efficient pace of work by managing project timelines, coordinating project team members, and providing timely updates to stakeholders
• Work effectively within cross-functional, global teams (including business domain experts, product owners, decision science engineers, and IT) to design, develop, deploy, and sustain operations research-based solutions that are scalable and with commercial-grade quality

About You

Skills and Qualifications

• Bachelors or Master’s degree preferred in Industrial Engineering or Applied Mathematics (or relevant field)
• Ability to translate general requirements and long-term deadlines into shorter-term work tasks, self-direct work, and monitor progress
• Solicits inputs from subject matter experts (SMEs) and engages with cross-functional teams to drive results
• Competent in developing mathematical optimization models using mathematical modeling languages such as AIMMS, GAMS, AMPL, Pyomo, Gurobipy, etc.
• Competent in developing system dynamics simulation models using software such as Stella Architect, VenSim, AnyLogic, etc.
• 5+ years’ experience in applying operations research modeling methods (mathematical optimization and/or stochastic simulation) for commercial-grade quality solutions
• Curious mindset in understanding business problems and their related factors to develop solutions
• Ability to view complex subjects from both a high level and detailed perspective, and communicate appropriately with different audiences

Skills and Qualifications

• Familiarity with developing discrete event simulation models using software such as Arena, Simio, etc.
• Familiarity with Python, especially for developing and deploying operations research solutions
• Experience with source code version control (Git)
• Strong written and verbal communication skills

Your benefits

An ExxonMobil career is one designed to last. Our commitment to you runs deep our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you: 

• Competitive compensation 
• Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits 
• Retirement benefits 
• Global networking & cross-functional opportunities
• Annual vacations & holidays
• Day care assistance program
• Training and development program
• Tuition assistance program
• Workplace flexibility policy
• Relocation program
• Transportation facility

Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company’s eligibility guidelines.

Stay connected with us

• Learn more about ExxonMobil in India, visit ExxonMobil India and Energy Factor India .
• Follow us on LinkedIn and Instagram
• Like us on  Facebook
• Subscribe our channel at YouTube

EEO Statement

ExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or disability status.
 

Business solicitation and recruiting scams

ExxonMobil does not use recruiting or placement agencies that charge candidates an advance fee of any kind (e.g., placement fees, immigration processing fees, etc.). Follow the LINK to understand more about recruitment scams in the name of ExxonMobil.
 

 

Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship. 

Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.

Drive the next wave of generative and multimodal intelligence that powers our autonomous drywall-finishing robots. As a core member of the AI Research team, you'll turn cutting-edge vision-language and diffusion advances into robust, real-time systems that see, reason, and act on dynamic construction sites.

Key Responsibilities

* Research & innovate diffusion-based generative models for photorealistic wall-surface simulation, defect synthesis, and domain adaptation.

* Architect and train Vision-Language Models (VLMs) and Vision-Language Alignment (VLA) objectives that connect textual work orders, CAD plans, and sensor data to pixel-level understanding.

* Lead development of auto-annotation pipelines (active learning, self-training, synthetic data) that scale to millions of frames and point-clouds with minimal human effort.

* Optimize and compress models (INT8, LoRA, distillation) for deployment on Jetson-class edge devices under ROS 2.

* Own the full lifecycle—problem definition, literature review, prototyping, offline/online evaluation, and production hand-off to perception & controls teams.

* Publish internal tech reports and external conference papers; mentor interns and junior engineers.

Qualifications & Skills

* 3+ years in deep-learning R&D or Ph.D./M.S. in CS, EE, Robotics or related field with strong publication record.

* Demonstrated expertise in diffusion models (DDPM, LDM, ControlNet) and multimodal transformers / VLMs (CLIP, BLIP-2, LLaVA, Flamingo).

* Proven success building large-scale data-centric AI workflows—active learning, pseudo-labeling, weak supervision.

* Advanced proficiency in Python, PyTorch (or JAX), experiment tracking, and scalable training (PyTorch Lightning, DeepSpeed, Ray).

* Familiarity with edge-AI runtimes (TensorRT, ONNX Runtime), and CUDA / C++ performance tuning.

* Strong mathematical foundation (probability, information theory, optimization) and ability to translate theory into production code.

* Bonus: experience with synthetic data generation in Isaac Sim, or robotics perception stacks (ROS2, Nav2, MoveIt 2, Open3D).

Why join us?

* Own breakthrough tech from idea to autonomous robot on active job-sites—your work leaves the lab fast.

* Collaborate cross-functionally with perception, controls, and product teams & publish at top venues with company support.

* Shape an industry by replacing dangerous, repetitive construction labor with intelligent robots.

* Competitive salary + equity, hardware budget, flexible hybrid work, and a culture that prizes deep work and rapid iteration.

Requirements

• Vision-Language Models
• Vision-Language Alignment
• R&D
• Ph.D./M.S. in CS, EE, Robotics
• TensorRT,
• ONNX Runtime
• CUDA / C++

Candidate should be able to:
•determines and recommends the appropriate method of research to investigate specific user experience issues or problems on the website. •designs research studies to collect customer behavioral data for use in the identification and analysis of technical customer solutions.
•consults with internal subject matter experts and third-party research vendors to assist in identifying the best approach to solving user experience issues.
•determine and collect the relevant data required to perform analyses and is also responsible for summarizing and communicating the results of the analyses to key stakeholders throughout the organization.
•perform several duties to support the UX Research function, including tasks like determining project methodology and approach, managing research projects, analyzing and interpreting data, reporting results, and providing recommendations to application design and product teams.
•Acquire, maintain and apply specific knowledge of relevant technical systems supporting research efforts.
•Design studies or construct surveys to answer research questions.
•Gather and compile relevant data for inclusion in presentations to explain findings, educate stakeholders, and offer actionable recommendations.
•Perform statistical analyses of large datasets.
•Compiles informative reports that include video and audio clips from qualitative studies.
•Identify and work with all affected groups and functions to support project impact
Scope, design, build and test studies in our online research platform.
Manage multiple research projects simultaneously.
•Keep up with research trends and best practices; develop industry knowledge and expertise.
•Design and implement communication plans.
Candidate should have:
•Minimum of five years of research design and implementation
•Bachelor' s degree required;Master's degree preferred
•Psychology, HCI, or related social sciences field with demonstrable academic experience with experimental design and statistical analysis.
•Excellent working knowledge of Adobe design tools-Photoshop, XD, Dreamweaver and adobe Illustrator
•Qualtrics experience. Someone well-versed in Qualtrics functionality building surveys, reporting, etc. Can build independently if given an assignment. We have a lot of surveys in another tool that needs to be rebuilt in Qualtrics.