954 Machine Learning jobs in Bangalore
Machine Learning Engineer
Posted 5 days ago
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NetApp is seeking an ML engineer to join the Data Services organization. The overarching vision of this organization is to empower organizations to effectively manage and govern their data estate and build cyber-resiliency while accelerating their digital transformation journey. To get to this vision, we will embark on an AI-first approach to build and deliver world-class suite of data services. As a key ML engineer in this initiative, the candidate will be responsible for independently deploying scalable AI/ML-based solutions, leveraging advancements in AI to solve real-world challenges in the domains of data protection and cyber-security. The candidate will possess deep expertise in using modern AI/ML systems to ship impactful products to production. This is going to be a challenging and a fun role in one of the most exciting roles in the industry today.
**Job Requirements**
+ Lead the development and deployment of AI/ML systems for Data protection with techniques from the realm of classical Machine learning, Generative AI and AI agents.
+ Develop scalable data pipelines for various AI/ML-driven solutions from building curated data pipelines, setting up automated evals, adopting latest and greatest inferencing platforms for rapid iterations.
+ Collaborate with data scientists and engineers to integrate AI into the broader products at NetApp. Effectively communicate complex technical artifacts to both technical and non-technical audiences.
+ Work with a great deal of autonomy and proactively bring open-source AI innovations into our research and experimentation roadmap. Ensure scalability, reliability, and performance of AI models in production environments.
+ Have a customer focus mindset and build AI/ML products that delight our customers.
+ Represent NetApp as an innovator in the machine learning community and promote the company's product capabilities in industry/academic conferences.
**Job Expectations**
+ The position is a Hybrid position, and the candidate is expected to work in NetApp Bangalore office at least two days a week.
**Required and Preferred Qualification**
+ Master's degree in computer science / applied mathematics / statistics / data science or equivalent experience.
+ 3+ years of experience in building MLOps pipelines, CI/CD pipelines, and ML systems lifecycle management.
+ Strong knowledge of optimizing and shipping machine learning and deep learning models to production.
+ Proficiency in Python, SQL and at least one cloud platform (AWS, Azure or GCP).
+ Excellent communication and collaboration skills, with demonstrated ability to work effectively with cross-functional teams and stakeholders of an organization
**Preferred Qualification**
+ 1+ years of experience in data engineering, including building and optimizing data pipelines and architectures.
+ Solid understanding of data science fundamentals and model evaluations, including supervised and unsupervised machine learning algorithms (both machine learning and deep learning).
+ Good understanding of cyber-security and data protection frameworks.
+ Experience of representing your work or company at AI/ML conferences.
+ Active GitHub profile showcasing relevant open-source AI/ML projects or Kaggle achievements.
At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process.
**Equal Opportunity Employer:**
NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, and any protected classification.
**Why NetApp?**
We are all about helping customers turn challenges into business opportunity. It starts with bringing new thinking to age-old problems, like how to use data most effectively to run better - but also to innovate. We tailor our approach to the customer's unique needs with a combination of fresh thinking and proven approaches.
We enable a healthy work-life balance. Our volunteer time off program is best in class, offering employees 40 hours of paid time off each year to volunteer with their favourite organizations. We provide comprehensive benefits, including health care, life and accident plans, emotional support resources for you and your family, legal services, and financial savings programs to help you plan for your future. We support professional and personal growth through educational assistance and provide access to various discounts and perks to enhance your overall quality of life.
If you want to help us build knowledge and solve big problems, let's talk.
Manager, Machine Learning
Posted 5 days ago
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Job Description
Every day, millions of posts, videos, and articles course through the LinkedIn feed, generating tens of thousands of comments every hour - and tens of millions more shares and likes.
Join the LSS-AI team and help create meaningful impact by connecting sellers and buyers to mutual growth opportunities! LinkedIn Sales Solutions (LSS) is one of the fastest-growing multi-billion dollar verticals at LinkedIn, and the LSS-AI team is at the forefront of building the next generation of AI-centric Sales Navigator platform. This platform enables tens of millions of companies to connect with their future customers, driving significant economic value. As a member of the LSS-AI team, you will work on cutting-edge projects, including building Agentic and GenAI-powered search and recommendation systems, tuning and applying domain-specific LLMs, and collaborating with our partner vendors like OpenAI. You will have the opportunity to work with passionate AI engineers, as well as our brilliant cross-functional partner teams in Engineering, Product Management, and Design. Together, we are creating immense economic value for our customers using the largest global professional economic graph.
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
As part of a new and fast growing team of top-notch scientists and engineers, you will experience all the excitement and dynamism of a startup along with the scale and technology of a world-class enterprise.
Responsibilities:
+ As a Manager, you will participate in key technical and design discussions with technical leads in the team.
+ You will lead the AI strategy for an area and work with the engineering and product leads to align it with the larger vision for the LinkedIn Sales ecosystem.
+ You will collaborate with application engineering, product, and partner teams to design machine learning solutions to power LSS products.
+ You will attract world class talent and provide technical guidance, career development, and mentoring to team members.
+ You will hold the team to a high quality bar for machine learning tech and actively reduce tech debt, designing systems that scale with algorithms and with time, and improve engineering productivity.
+ You will partner with data science & analytics teams, product & infrastructure teams to build and onboard new modeling use cases online.
Basic Qualifications:
+ MS/PhD degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related discipline.
+ 8+ years of experience in machine learning, artificial intelligence, or related fields.
+ 5+ years in an architect or technical leadership role driving large-scale AI initiatives.
+ Hands-on experience with end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and optimization.
+ Experience of leading a team of engineers as a people manager.
+ 1+ year(s) of management experience or 1+ year(s) of staff level experience with management training
Preferred Qualifications:
+ 3+ years of management experience.
+ MS or PhD in Computer Science, Statistics or related technical discipline
+ Experience with machine learning, optimization algorithms, and/or deep-learning techniques
+ Experience developing large scale systems
+ Leadership or mentorship experience is preferred
+ Analytical approach coupled with solid communication skills and a sense of ownership
+ Track record of producing papers in conferences such as KDD, . and Patenting Innovations
You will Benefit from our Culture:
We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels
Suggested Skills
People Management
Clustered computing systems experience
Experience in building ML data systems
**India Disability Policy**
LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit Data Privacy Notice for Job Candidates **
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants:
Machine Learning Engineer
Posted 1 day ago
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About the Company:
UptimeAI is leading the way in predictive analytics and AI-driven solutions to optimize operational uptime and reduce downtime for industrial and enterprise clients. Our innovative platform harnesses cutting-edge data science to deliver actionable insights, ensuring maximum efficiency and reliability. UptimeAI uniquely combines Artificial Intelligence with Subject Matter Knowledge from 200+ years of cumulative experience to explain interrelations across upstream/downstream equipment, adapt to changes, identify problems, and give prescriptive diagnosis like a human expert would.
About the Role:
We're looking for a highly skilled and hands-on ML End-to-End Engineer. You'll need deep practical experience across the entire machine learning lifecycle, from data ingestion and model development to robust backend integration and scalable production deployment. We want someone who not only understands the theory but can demonstrate significant real-world application and problem-solving at every stage of ML product development.
Responsibilities:
- ML Model Development & Optimization:
- Algorithm Proficiency: Proven experience designing, training, and optimizing diverse ML models, including strong expertise in supervised learning, and significant practical experience with unsupervised learning (e.g., clustering, dimensionality reduction, anomaly detection) and reinforcement learning algorithms (e.g., Q-learning, policy gradients). You should be able to discuss specific challenges encountered during model development across these paradigms and how you resolved them.
- Frameworks: Hands-on expertise with PyTorch, TensorFlow, and scikit-learn.
- Libraries: Strong proficiency with NumPy, Pandas, SciPy, Seaborn, and Plotly for data manipulation, analysis, and visualization.
- Feature Engineering: Demonstrable experience in effective feature engineering, selection, and transformation techniques.
- Data Engineering & Management for ML:
- Data Pipelining: Proven experience building and managing robust data pipelines for ML, including data ingestion, cleaning, transformation, and validation.
- Database Proficiency: Strong command of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB) for storing and retrieving data relevant to ML models.
- Real-time Data Streams: Expertise with Apache Kafka for building and managing real-time data ingestion and processing pipelines.
- Backend Development for ML Applications:
- API Development: Demonstrable experience designing, building, and maintaining RESTful APIs for serving ML model predictions.
- Programming Language & Frameworks: Strong proficiency in Python with practical experience using either Flask or FastAPI for backend service development.
- System Design: Ability to design scalable, fault-tolerant, and high-performance backend systems to support ML inference.
- MLOps & Production Deployment:
- Containerization: Expertise in containerization technologies (e.g., Docker) for packaging ML models and their dependencies.
- Orchestration: Experience with container orchestration tools (e.g., Kubernetes) for deploying and managing ML services at scale.
- CI/CD for ML: Proven ability to set up and manage CI/CD pipelines specifically for ML model training, testing, and deployment (e.g., Jenkins, GitLab CI, GitHub Actions).
- Monitoring & Logging: Experience in implementing robust monitoring, alerting, and logging solutions for production ML systems to ensure performance, reliability, and data drift detection
- Model Performance & Reliability:
- Performance Tuning: Proven ability to identify and resolve performance bottlenecks in ML models and backend services. This includes experience with fine-tuning models and applying techniques to extract maximum performance from them, such as quantization, pruning, or model compression.
- Model Versioning & Experiment Tracking: Experience with tools and practices for model versioning, experiment tracking (e.g., MLflow, DVC), and reproducibility.
- General Engineering & Problem Solving:
- Competitive Coding / Algorithmic Problem Solving: Demonstrated proficiency in competitive coding platforms (e.g., LeetCode, HackerRank, TopCoder, Codeforces) or a strong, demonstrable foundation in algorithms and data structures, showcasing exceptional problem-solving abilities.
- Security Best Practices for ML Systems: Understanding and implementation of security best practices for ML models, data, and APIs.
Qualifications:
- 5+ years of experience as ML Engineer in high-growth SaaS or product startups
- Strong problem-solving and engineering mindset, with a keen eye for scalability, reliability, and efficiency.
- Excellent communication skills for conveying complex technical information to both technical and non-technical stakeholders.
- Adaptable and enthusiastic about working in a fast-paced, product-driven environment.
- Proactive in learning new ML technologies, backend frameworks, and deployment methodologies
- Comfortable working in a fast-paced, ambiguous startup environment
Why to join UptimeAI:
- Impact Industry-Wide Change: Contribute to transformative solutions that significantly improve operational efficiency and reliability for global clients.
- Collaborative and Growth-Oriented Environment: Join a talented, passionate team that values innovation, continuous learning, and professional growth.
- Opportunities for Leadership and Innovation: Lead pioneering projects, influence product development, and shape the future of industrial AI solutions.
Pay range and compensation package:
(Pay range or salary or compensation)
Equal Opportunity Statement:
(Include a statement on commitment to diversity and inclusivity.)
Machine Learning Engineer
Posted 1 day ago
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Job Description
Hiring: Machine Learning Engineers (ML 2 / ML 3) – Bangalore
Are you passionate about building customer-facing AI solutions that make a real impact?
Do you thrive in fast-paced, product-driven environments where ownership and accountability are valued?
We are looking for ML Engineers (Level 2/3) to join our growing AI/ML team in Bangalore. This is an exciting opportunity to work on Generative AI, personalization, and intelligent search systems that will directly shape the experience of millions of users.
Key Responsibilities
As a part of our ML team, you will:
- Design and implement scalable ML solutions that directly align with product and business goals.
- Develop, test, and optimize ML models for production environments with high availability and low latency.
- Build Generative AI features such as conversational interfaces, intelligent assistants, and personalized experiences.
- Partner with product managers, data scientists, and engineers to integrate ML into customer-facing applications .
- Monitor and evaluate model performance post-deployment; iterate to improve accuracy, latency, and UX.
- Drive best practices in experimentation, reproducibility, and deployment workflows .
- Participate actively in code reviews, design discussions, and technical deep dives .
- Work closely with stakeholders to translate business needs into ML-driven solutions .
Machine Learning Engineer
Posted 1 day ago
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Job Description
Generative AI & LLM Specialist
Experience: 3-6 Years
Location: Bangalore
Type: Full-time - Hybrid
The Opportunity
We’re seeking a Generative AI & LLM Specialist with deep expertise in building with LLMs, Retrieval-Augmented Generation (RAG), Text-Augmented Generation (TAG), and agentic AI workflows. This person will play a key role in shaping and developing a platform to orchestrate and synchronize AI agents capable of performing complex, multi-step reasoning tasks and collaborating to deliver enterprise-grade services.
You’ll bring a rare blend of skills across Python, data science, and generative modeling, while also understanding how to structure systems that make intelligent agents work together reliably and safely.
Responsibilities
●Design, develop, and deploy core components of a platform to support agentic AI architectures, including agent orchestration, memory, and tool use.
●Implement synchronized multi-agent workflows that can reason, plan, and act toward shared goals.
●Work with and fine-tune foundation models, build advanced pipelines with RAG/TAG, and embed them into real-world applications.
●Build reusable primitives for application developers to easily extend and customize agent capabilities.
●Integrate LLM-based agents with tools, APIs, knowledge bases, and vector databases to expand reasoning and execution capabilities.
●Contribute to system design for scalability, performance, and security in a production-grade AI service platform.
●Collaborate across engineering, product, and design to rapidly prototype and launch intelligent features.
●Monitor emerging research in agent-based AI, model alignment, and cognitive architectures—and translate insights into product capabilities.
Qualifications
●Education: Bachelors or Masters in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
●Experience: 3–6 years of experience with Generative AI, LLMs, and advanced NLP.
Technical Skills:
- Deep understanding of agentic AI concepts, such as autonomous agents, tool use, memory/reasoning modules, and planning.
- Proficient in Python and GenAI frameworks: HuggingFace, LangChain, LlamaIndex, OpenAI/Anthropic APIs, etc.
- Strong grasp of Data Science, particularly NLP, ML model evaluation, and experimental design.
- Experience with multi-agent coordination, decision-making systems, or distributed AI architectures is highly desirable.
- Exposure to enterprise software development—REST APIs, distributed systems, backend services, and cloud platforms.
- Familiarity with orchestration tools like Celery, Airflow, or agent frameworks like CrewAI, Autogen, or custom setups.
- Passion for working in an early-stage, high-impact environment where speed, creativity, and collaboration matter
Soft Skills :
- Excellent communication and problem-solving abilities.
- Ability to work independently and as part of a team.
Nice-to-Haves
● Background in cognitive architectures, reinforcement learning, or multi-modal systems.
● Contributions to open-source projects in GenAI or agentic AI.
● Experience with vector stores (e.g., FAISS, Weaviate, Pinecone) and graph-based reasoning.
● Previous startup and 0-to-1 product experience.
Machine Learning Engineer
Posted 1 day ago
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Job Description
Company Description
Cache Technologies & Communications Pvt. Ltd. is an information technology services and solutions company based in Bangalore, India. Our mission is to help companies become more responsive, productive, and resilient through advanced business technologies. We provide comprehensive solutions encompassing servers, data center facilities, software, storage, and networking. Our competencies include IT optimization, enterprise security, business continuity, disaster recovery, content management, business integration, and business intelligence.
Machine Learning Engineer
Posted 1 day ago
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Job Description
TE-4 Years and above
Location- Bangalore/Chennai/Hyderabad
NP- 15-30 Days max
JOB DESCRIPTION
Join our fast‑growing team to build a unified platform for data analytics, machine learning, and generative AI. You’ll integrate the AI/ML toolkit, real‑time streaming into a backed feature store, and dashboards—turning raw events into reliable features, insights, and user‑facing analytics at scale.
What you’ll do
- Design and build streaming data pipelines (exactly‑once or effectively‑once) from event sources into low‑latency feature serving and NRT and OLAP queries.
- Develop an AI/ML toolkit: reusable libraries, SDKs, and CLIs for data ingestion, feature engineering, model training, evaluation, and deployment.
- Stand up and optimize a production feature store (schemas, SCD handling, point‑in‑time correctness, TTL/compaction, backfills).
- Expose features and analytics via well‑designed APIs/Services; integrate with model serving and retrieval for ML/GenAI use cases.
- Build and operationalize Superset dashboards for monitoring data quality, pipeline health, feature drift, model performance, and business KPIs.
- Implement governance and reliability: data contracts, schema evolution, lineage, observability, alerting, and cost controls.
- Partner with UI/UX, data science, and backend teams to ship end‑to‑end workflows from data capture to real‑time inference and decisioning.
- Drive performance: benchmark and tune distributed DB (partitions, indexes, compression, merge settings), streaming frameworks, and query patterns.
- Automate with CI/CD, infrastructure‑as‑code, and reproducible environments for quick, safe releases.
Tech you may use
Languages: Python, Java/Scala, SQL
Streaming/Compute: Kafka (or Pulsar), Spark, Flink, Beam
Storage/OLAP: ClickHouse (primary), object storage (S3/GCS), Parquet/Iceberg/Delta
Orchestration/Workflow: Airflow, dbt (for transformations), Makefiles/Poetry/pipenv
ML/MLOps: MLflow/Weights & Biases, KServe/Seldon, Feast/custom feature store patterns, vector stores (optional)
Dashboards/BI: Superset (plugins, theming), Grafana for ops
Platform: Kubernetes, Docker, Terraform, GitHub Actions/GitLab CI, Prometheus/OpenTelemetry
Cloud: AWS/GCP/Azure
What we’re looking for
- 4+ years building production data/ML or streaming systems with high TPS and large data volumes.
- Strong coding skills in Python and one of Java/Scala; solid SQL and data modeling.
- Hands‑on experience with Kafka (or similar), Spark/Flink, and OLAP stores—ideally ClickHouse.
- GenAI pipelines: retrieval‑augmented generation (RAG), embeddings, prompt/tooling workflows, model evaluation at scale.
- Proven experience designing feature pipelines with point‑in‑time correctness and backfills; understanding of online/offline consistency.
- Experience instrumenting Superset dashboards tied to ClickHouse for operational and product analytics.
- Fluency with CI/CD, containerization, Kubernetes, and infrastructure‑as‑code.
- Solid grasp of distributed systems and architecture fundamentals: partitioning, consistency, idempotency, retries, batching vs. streaming, and cost/perf trade‑offs.
- Excellent collaboration skills; ability to work cross‑functionally with DS/ML, product, and UI/UX.
- Ability to pass a CodeSignal prescreen coding test.
Grid Dynamics (Nasdaq:GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, India, Central and Eastern Europe.
To learn more about Grid Dynamics, please visit . Follow us on Facebook , Twitter , and LinkedIn .
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Machine Learning Engineer
Posted 1 day ago
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Senior Software Engineer -Job Description
Are you excited about the transformative power of ecommerce in changing the landscape of
grocery retail in India? bigbasket is creating milestones in the online grocery market and has
recently re-hauled its supply chains across cities to fulfil many customer orders faster. The
company’s operations have expanded to more than 60 cities in India, recording about 15
million customer orders per month.
The engineering team thrives on out of the box thinking and relentless pursuit of excellence.
While we are techies at heart -- we don't use technology for the sake of technology but
pride ourselves in solving customer problems in the most efficient and elegant ways. Do the
customers really care about efficient implementation of Levenshtein Distance? Well no. But
they really appreciate when their typos are pardoned and don't get in the way.
As a Software Engineer we are looking for developers who share our passion for building
world class software.If you are excited about the prospect of changing the way India shops
for groceries and being a pioneer – then this a great home for you. Not to mention the thrill
of building products that millions use daily and using cutting edge technology to make the
products customers love.
What would you be doing/ Expected from this role?
• Collaborate with cross-functional teams including data scientists, engineers, and product managers to deliver AI-driven solutions.
• Drive the architecture of machine learning pipelines from data collection and preprocessing to model training, evaluation, and deployment.
• Implement scalable machine learning solutions using cloud infrastructure (AWS, GCP, Azure) and big data technologies (Spark, Hadoop).
• Develop and maintain model monitoring, alerting systems, and frameworks to ensure optimal performance in production.
• Stay up to date with the latest trends in AI and machine learning, identifying opportunities for innovation and improvement.
• Work on improving model interpretability, fairness, and bias mitigation in
alignment with ethical AI practices.
• Collaborate on the development of internal tools and libraries that facilitate the use of machine learning models across the organization.
• Conduct code reviews, optimize algorithms, and ensure the scalability and reliability of machine learning systems.
Preferred Skills:
• Experience in LLM technologies, computer vision and ML algorithms.
• Knowledge of data governance and ethical AI principles.
• Familiarity with real-time data streaming technologies (Kafka, Flink, etc.).
Who are we looking for?
• Bachelor’s degree in computer science or equivalent practical experience.
•Must be able to work independently and enjoy working at a fast-paced start-up
environment who is adept at experimenting with new technologies.
• Must have excellent communication (verbal & written), interpersonal, leadership, and problem-solving skills.
Machine Learning Engineer
Posted 1 day ago
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Job Title: Machine Learning Engineer (Founding Engineer)
Location: Bangalore, INDIA
Experience Level: Mid to Senior (3–5 years)
About Nexie
We’re building an AI-first platform that transforms how ecommerce brands connect with customers. Our agentic AI goes beyond simple automation — it thinks, creates, and adapts in real time to drive growth. The mission: make marketing feel effortless and intelligent.
Why Join
- Founding seat → shape the product & culture from scratch
- Work directly with serial founders (past startup → exit)
- Real equity + Competitive salary
- Build fast, ship fast, impact global brands
Your Role
- Own ML infra end-to-end: data → model → production
- Work on LLMs, embeddings, feedback loops, decision engines
- Rapid prototyping, user-driven iteration
- Push boundaries of AI agents in marketing
You Bring
- 3–5 yrs ML engineering (Python, PyTorch/TensorFlow, LLM APIs)
- Built & shipped ML systems (not just notebooks)
- Comfort with ambiguity, love for zero→one building
Bonus
- Agent systems / reasoning frameworks
- Ecommerce or martech exposure
- Interest in design/UX
We Value
Builders > employees. You’re curious, scrappy, and want to see your code shape the company’s DNA.
DM us or apply if you’re ready to build AI from the ground up.
Machine Learning Engineer
Posted 1 day ago
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Company Description
Ai Health Highway is a global team of medical professionals, signal processing engineers, data scientists, and clinicians. The company is AI-first and focused on making screening of chronic diseases cost-effective at the primary care clinic. This approach aims to improve patient outcomes and accessibility to healthcare services.
We are backed by Turbostart, Rainmatter by Zerodha, The Chennai Angels, Social Alpha, Foundation for Science, Innovation & Development (FSID) IISC and many other prominent angel investors. AiSteth is one of the 27 most promising ML startups selected for AWS ML Elevate 2022 program by Amazon, Intel, Accel & YourStory. We are also the winners of the PHC Tech Challenge 2021 award organized by PATH.
Goal - Our Goal is to reduce 30% premature deaths due to #NCDs by 2030.
Role Description - ML Engineer (Bangalore / On-Site)
- Work closely with the Product leader to define product/platform vision
- Interface with Client ML and Business teams to demonstrate thought leadership, and drive delivery of products and solutions
- Conduct original research on large proprietary and open source data sets
- Identify, research, prototype and build predictive models
- Create framework for AI/ML code deployment to ensure robustness and reliability of production ready models
- Responsible for understanding industry processes and incorporating them in the solution
- Be responsible for measuring and optimizing the quality of your algorithms
- Collaborate with engineering teams, platform teams to drive vision for AI/ML platform
Qualifications
- Minimum 2-3 years of experience working in similar field/ domain.
- Advanced degree in Computer Science, Signal Processing, Data science, Biomedical Engineering, AI/ML
- At least one core programming expertise, such as python (Tensorflow, Keras, Pytorch, Signal Processing packages etc.), R, Scala
- Strong statistical knowledge, analytical and problem-solving skills, intuition and experience applying machine learning models to real world data
- Strong project management skills to execute multiple projects in parallel
- Experience in deploying production ready ML code.
- Experience with knowledge graphs, optimization, decision theory or signal processing
- Interpersonal skills: good verbal and written communication skills, cross-group and cross-culture collaboration.
- Understanding of Algorithms and Machine Learning principles
- Experience with healthcare data analysis is a plus