3,477 Research Engineer jobs in India

Key Responsibilities:

Model Development & Optimization

• Design and implement AI/ML models for online spectacles centration, fitting and online refraction.
• Develop models for online visual acuity assessment, screen-based testing, or optical prescription estimation.
• Develop models that replaces and enhances online measurement approaches through innovative data and AI-supported methods. With the midterm goal: Data replaces measurement.
• Implement and launch AI based solutions, fulfilling regulatory and legal requirements.

Data Handling & Preprocessing

• Work with multi-modal datasets
• Ensure that necessary data is gathered accurately and efficiently.
• Annotate, normalize, and augment vision-related data for robust model training.

Collaboration & Validation

• Collaborate with vision science experts, optometrists, and product teams to align on accuracy and reliability metrics.
• Validate AI models through lab or clinical studies when applicable.

Documentation & Compliance

• Ensure proper documentation of models, data practices, and support regulatory alignment (e.g., MDR, HIPAA, DPDPA, GDPR if applicable).

Minimum Qualification:

• Education : Master's (preferred) or Bachelor’s in Computer Science, AI, Biomedical Engineering, Applied Physics, or related fields.

• Experience : 2+ years of experience in AI/ML, with at least 1 year in or healthcare/vision-based applications .

Core Technical Skills (Must-Have):

• Programming- Python (must), OpenCV, NumPy, Pandas
• ML/DL Frameworks- TensorFlow, PyTorch, scikit-learn, Keras
• Mathematical Foundations- Linear algebra, optimization, statistical signal processing
• Data Handling- Image/video pipeline handling, image annotation tools, real-time stream processing
• Version Control- Git, Jupyter, API documentation best practices

Position: NLP Research Engineer

Location: On-site, HSR Layout, Benagluru.

Type: Full Time

About the Role:

We are seeking a driven NLP Research Engineer with 2–3 years of hands-on experience in model development and prototyping. In this R&D-focused role, you will explore and implement state-of-the-art LLM architectures, prompt engineering strategies, and LLM training techniques tailored to healthcare and oncology text. Your primary responsibility is to drive proof-of-concepts—from rapid iterations to rigorous experimental evaluations on clinical-text tasks. While our production teams will help with deployment, you’ll collaborate closely to hand off scalable prototypes that demonstrate clear performance gains.

What We Expect You to Bring:

• Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, AI/ML, or a related field
• 2–3 years of professional R&D experience in NLP or ML research roles
• Strong Python skills and deep familiarity with PyTorch or TensorFlow
• Proficiency in working with NLP frameworks (e.g., spaCy, NLTK, HuggingFace Transformers, LangChain, vectorDBs, etc), deep learning libraries (e.g., PyTorch), and common data preprocessing techniques.
• Expertise in prompt engineering, few-shot learning, and fine-tuning for domain-specific tasks
• Familiarity with building retrieval-augmented generation (RAG) pipelines.
• Hands-on experience with LLM fine-tuning using LoRA and SFT methods
• Solid understanding of experimental design, ablation studies, and statistical significance testing
• Familiarity with clinical or biomedical NLP is a plus
• If you have worked with Direct Preference Optimization (DPO), that’s a plus
• Excellent communication skills for sharing insights in seminars, whitepapers, or publications

What You Will Be Doing:

• Model Innovation & Prototyping: Rapidly prototype novel LLM architectures, adapter modules, and prompt-tuning strategies for tasks such as clinical note summarization, entity extraction, and question answering.
• Experimental Design & Analysis: Define evaluation protocols, run ablation studies, and analyze results to quantify improvements in accuracy, robustness, and domain generalization.
• Proof-of-Concept Development: Build end-to-end POCs demonstrating how research breakthroughs translate into tangible gains on real healthcare datasets.
• Collaboration & Knowledge Sharing: Work alongside NLP engineers and MLOps teams to hand off production-ready prototypes; present findings in regular research seminars and contribute to internal or external publications.
• Literature & Trend Monitoring: Continuously survey the latest NLP/ML research, distill key innovations, and propose experiments to test applicability in our clinical environment.

Why Join?

• We are revolutionizing a unique industry that has the potential to impact and benefit patients from all over the world - you can create impact at scale.
• We have access to the best computing resources available, including the H100 and A100, among others.
• We have had company-sponsored workations in Bali, Sri Lanka, and Manali and take pride in our hard-working yet super fun culture.
• We are working on a few of the most challenging problems in a highly regulated industry, which provides you with an opportunity to solve some of the most interesting things.
• You will get a chance to work with experts from multiple industries, the best in the industry compensation, and to continue building your own (and, of course, new) projects.

Key Responsibilities:

Model Development & Optimization

• Design and implement AI/ML models for online spectacles centration, fitting and online refraction.
• Develop models for online visual acuity assessment, screen-based testing, or optical prescription estimation.
• Develop models that replaces and enhances online measurement approaches through innovative data and AI-supported methods. With the midterm goal: Data replaces measurement.
• Implement and launch AI based solutions, fulfilling regulatory and legal requirements.

Data Handling & Preprocessing

• Work with multi-modal datasets
• Ensure that necessary data is gathered accurately and efficiently.
• Annotate, normalize, and augment vision-related data for robust model training.

Collaboration & Validation

• Collaborate with vision science experts, optometrists, and product teams to align on accuracy and reliability metrics.
• Validate AI models through lab or clinical studies when applicable.

Documentation & Compliance

• Ensure proper documentation of models, data practices, and support regulatory alignment (e.g., MDR, HIPAA, DPDPA, GDPR if applicable).

Minimum Qualification:

• Education: Master's (preferred) or Bachelor’s in Computer Science, AI, Biomedical Engineering, Applied Physics, or related fields.

• Experience: 2+ years of experience in AI/ML, with at least 1 year in or healthcare/vision-based applications.

Core Technical Skills (Must-Have):

• Programming- Python (must), OpenCV, NumPy, Pandas
• ML/DL Frameworks- TensorFlow, PyTorch, scikit-learn, Keras
• Mathematical Foundations- Linear algebra, optimization, statistical signal processing
• Data Handling- Image/video pipeline handling, image annotation tools, real-time stream processing
• Version Control- Git, Jupyter, API documentation best practices

Position: NLP Research Engineer

Location: On-site, HSR Layout, Benagluru.

Type: Full Time

About the Role:

We are seeking a driven NLP Research Engineer with 2–3 years of hands-on experience in model development and prototyping. In this R&D-focused role, you will explore and implement state-of-the-art LLM architectures, prompt engineering strategies, and LLM training techniques tailored to healthcare and oncology text. Your primary responsibility is to drive proof-of-concepts—from rapid iterations to rigorous experimental evaluations on clinical-text tasks. While our production teams will help with deployment, you’ll collaborate closely to hand off scalable prototypes that demonstrate clear performance gains.

What We Expect You to Bring:

• Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, AI/ML, or a related field
• 2–3 years of professional R&D experience in NLP or ML research roles
• Strong Python skills and deep familiarity with PyTorch or TensorFlow
• Proficiency in working with NLP frameworks (e.g., spaCy, NLTK, HuggingFace Transformers, LangChain, vectorDBs, etc), deep learning libraries (e.g., PyTorch), and common data preprocessing techniques.
• Expertise in prompt engineering, few-shot learning, and fine-tuning for domain-specific tasks
• Familiarity with building retrieval-augmented generation (RAG) pipelines.
• Hands-on experience with LLM fine-tuning using LoRA and SFT methods
• Solid understanding of experimental design, ablation studies, and statistical significance testing
• Familiarity with clinical or biomedical NLP is a plus
• If you have worked with Direct Preference Optimization (DPO), that’s a plus
• Excellent communication skills for sharing insights in seminars, whitepapers, or publications

What You Will Be Doing:

• Model Innovation & Prototyping: Rapidly prototype novel LLM architectures, adapter modules, and prompt-tuning strategies for tasks such as clinical note summarization, entity extraction, and question answering.
• Experimental Design & Analysis: Define evaluation protocols, run ablation studies, and analyze results to quantify improvements in accuracy, robustness, and domain generalization.
• Proof-of-Concept Development: Build end-to-end POCs demonstrating how research breakthroughs translate into tangible gains on real healthcare datasets.
• Collaboration & Knowledge Sharing: Work alongside NLP engineers and MLOps teams to hand off production-ready prototypes; present findings in regular research seminars and contribute to internal or external publications.
• Literature & Trend Monitoring: Continuously survey the latest NLP/ML research, distill key innovations, and propose experiments to test applicability in our clinical environment.

Why Join?

• We are revolutionizing a unique industry that has the potential to impact and benefit patients from all over the world - you can create impact at scale.
• We have access to the best computing resources available, including the H100 and A100, among others.
• We have had company-sponsored workations in Bali, Sri Lanka, and Manali and take pride in our hard-working yet super fun culture.
• We are working on a few of the most challenging problems in a highly regulated industry, which provides you with an opportunity to solve some of the most interesting things.
• You will get a chance to work with experts from multiple industries, the best in the industry compensation, and to continue building your own (and, of course, new) projects.

Key Responsibilities:

Model Development & Optimization

• Design and implement AI/ML models for online spectacles centration, fitting and online refraction.
• Develop models for online visual acuity assessment, screen-based testing, or optical prescription estimation.
• Develop models that replaces and enhances online measurement approaches through innovative data and AI-supported methods. With the midterm goal: Data replaces measurement.
• Implement and launch AI based solutions, fulfilling regulatory and legal requirements.

Data Handling & Preprocessing

• Work with multi-modal datasets
• Ensure that necessary data is gathered accurately and efficiently.
• Annotate, normalize, and augment vision-related data for robust model training.

Collaboration & Validation

• Collaborate with vision science experts, optometrists, and product teams to align on accuracy and reliability metrics.
• Validate AI models through lab or clinical studies when applicable.

Documentation & Compliance

• Ensure proper documentation of models, data practices, and support regulatory alignment (e.g., MDR, HIPAA, DPDPA, GDPR if applicable).

Minimum Qualification:

• Education : Master's (preferred) or Bachelor’s in Computer Science, AI, Biomedical Engineering, Applied Physics, or related fields.

• Experience : 2+ years of experience in AI/ML, with at least 1 year in or healthcare/vision-based applications .

Core Technical Skills (Must-Have):

• Programming- Python (must), OpenCV, NumPy, Pandas
• ML/DL Frameworks- TensorFlow, PyTorch, scikit-learn, Keras
• Mathematical Foundations- Linear algebra, optimization, statistical signal processing
• Data Handling- Image/video pipeline handling, image annotation tools, real-time stream processing
• Version Control- Git, Jupyter, API documentation best practices

Position: NLP Research Engineer

Location: On-site, HSR Layout, Benagluru.

Type: Full Time

About the Role:

We are seeking a driven NLP Research Engineer with 2–3 years of hands-on experience in model development and prototyping. In this R&D-focused role, you will explore and implement state-of-the-art LLM architectures, prompt engineering strategies, and LLM training techniques tailored to healthcare and oncology text. Your primary responsibility is to drive proof-of-concepts—from rapid iterations to rigorous experimental evaluations on clinical-text tasks. While our production teams will help with deployment, you’ll collaborate closely to hand off scalable prototypes that demonstrate clear performance gains.

What We Expect You to Bring:

1. Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, AI/ML, or a related field
2. 2–3 years of professional R&D experience in NLP or ML research roles
3. Strong Python skills and deep familiarity with PyTorch or TensorFlow
4. Proficiency in working with NLP frameworks (e.g., spaCy, NLTK, HuggingFace Transformers, LangChain, vectorDBs, etc), deep learning libraries (e.g., PyTorch), and common data preprocessing techniques.
5. Expertise in prompt engineering, few-shot learning, and fine-tuning for domain-specific tasks
6. Familiarity with building retrieval-augmented generation (RAG) pipelines.
7. Hands-on experience with LLM fine-tuning using LoRA and SFT methods
8. Solid understanding of experimental design, ablation studies, and statistical significance testing
9. Familiarity with clinical or biomedical NLP is a plus
10. If you have worked with Direct Preference Optimization (DPO), that’s a plus
11. Excellent communication skills for sharing insights in seminars, whitepapers, or publications

What You Will Be Doing:

1. Model Innovation & Prototyping: Rapidly prototype novel LLM architectures, adapter modules, and prompt-tuning strategies for tasks such as clinical note summarization, entity extraction, and question answering.
2. Experimental Design & Analysis: Define evaluation protocols, run ablation studies, and analyze results to quantify improvements in accuracy, robustness, and domain generalization.
3. Proof-of-Concept Development: Build end-to-end POCs demonstrating how research breakthroughs translate into tangible gains on real healthcare datasets.
4. Collaboration & Knowledge Sharing: Work alongside NLP engineers and MLOps teams to hand off production-ready prototypes; present findings in regular research seminars and contribute to internal or external publications.
5. Literature & Trend Monitoring: Continuously survey the latest NLP/ML research, distill key innovations, and propose experiments to test applicability in our clinical environment.

Why Join?

1. We are revolutionizing a unique industry that has the potential to impact and benefit patients from all over the world - you can create impact at scale.
2. We have access to the best computing resources available, including the H100 and A100, among others.
3. We have had company-sponsored workations in Bali, Sri Lanka, and Manali and take pride in our hard-working yet super fun culture.
4. We are working on a few of the most challenging problems in a highly regulated industry, which provides you with an opportunity to solve some of the most interesting things.
5. You will get a chance to work with experts from multiple industries, the best in the industry compensation, and to continue building your own (and, of course, new) projects.

We are seeking a skilled and motivated LLM (Language Model) Engineer to join our dynamic team. As an LLM Engineer, you will play a crucial role in advancing our language-based projects, with a focus on Langchain and the OpenAI API. This is an excellent opportunity for individuals with a passion for language technology and a proven track record in working with cutting-edge language models. 

**Responsibilities:**

1. Collaborate with the development team to integrate and optimize language models within the Langchain platform.

2. Utilize your expertise in working with the OpenAI API to enhance the capabilities and performance of our applications.

3. Design, develop, and maintain language-based features, ensuring seamless integration and user-friendly experiences.

4. Participate in brainstorming sessions and provide innovative ideas for improving existing projects and developing new language-related initiatives.

5. Conduct thorough testing, debugging, and performance tuning to ensure the reliability and efficiency of the language models in various applications.

6. Stay up-to-date with the latest advancements in natural language processing and contribute insights to the team's knowledge base.

**Requirements:**

1. **Must have Masters Degree M-tech, Msc etc.**

2. Strong experience working with Langchain, OpenAI API, and other relevant language technologies.

3. Proficiency in programming languages commonly used in the field of natural language processing, such as Python, and frameworks like TensorFlow or PyTorch.

4. Solid understanding of linguistic principles and concepts, allowing you to fine-tune and customize language models effectively.

5. Proven ability to work independently, manage time efficiently, and deliver high-quality results within specified deadlines.

6. Excellent problem-solving skills, with a keen attention to detail and a drive to tackle complex challenges.

7. Effective communication and teamwork skills, enabling you to collaborate seamlessly with cross-functional teams.

8. Prior experience in contributing to open-source language projects or research efforts is a plus.

**Benefits:**

1. Competitive salary, commensurate with experience and commitment.

2. Opportunity to work with cutting-edge language technologies and contribute to innovative projects.

3. Flexibility in work hours, allowing you to balance your commitments with the role.

4. Exposure to a collaborative and dynamic work environment that encourages learning and growth.

5. Potential for skill enhancement and networking within the field of natural language processing and AI.

6. If you are enthusiastic about language technology, have a strong foundation in working with Langchain and the OpenAI API, and are looking for a part-time role that offers both flexibility and exciting challenges, we encourage you to apply for this position. Join our team and help shape the future of language-driven innovations.

Job Title: RL Research Engineer (Planning & Control)

Location: Vapi, Gujarat

Employment Type: Full-Time

Overview

We are seeking a highly skilled Reinforcement Learning (RL) Research Engineer specializing in planning and control. The role focuses on designing learning-based planners and policies (RL, imitation learning, model-based) and integrating them with classical control approaches to enable safe, efficient, and robust autonomous operation across multiple domains including humanoids, AGVs, cars, and drones.

Key Responsibilities

• Develop and train policies from human demonstrations and teleoperation data.
• Implement safe reinforcement learning approaches with constraints.
• Design long-horizon planners using world models and uncertainty-aware control.
• Implement safety shields, fallback controllers, and verify-before-deploy pipelines.
• Collaborate with cross-functional teams to integrate RL policies with control systems.
• Conduct sim-to-real transfer and ensure policies generalize in real-world settings.
• Design reward functions and implement offline RL and behavioral cloning strategies.

Must-Haves

• 4–8+ years of experience in RL and control systems.
• Strong expertise in Model Predictive Control (MPC), Control Barrier Functions (CBFs), reachability analysis, or similar methods.
• Master’s or PhD in Robotics, Control, AI, or a related field.
• Experience with sim-to-real transfer, reward design, offline RL, and behavioral cloning.

Nice-to-Haves

• Experience with multi-agent reinforcement learning.
• Knowledge of hierarchical options and diffusion policies.
• Familiarity with long-horizon task planning in complex environments.

Success Metrics

• Task success rate in target domains.
• Rate of human or system interventions during execution.
• Compliance with energy, jerk, and other control limits.
• Minimization of constraint violations in real-world deployment.

Domain Notes

Humanoids:

- Stable locomotion and bimanual task RL.

AGVs (Autonomous Ground Vehicles):

- Navigation in mixed human zones, traffic rule compliance, and aisle etiquette.

Cars:

- Interactive merges, handling unprotected turns, and safe navigation in dynamic traffic.

Drones:

- Wind-robust flight, safe landing and perching maneuvers.

Application Instructions

Interested candidates may apply by sending their resume and cover letter to with the subject line: “RL Research Engineer (Planning & Control) Application” .