AI Engineer

Pune - India

Monthly Salary: Not Disclosed

Experience Required: 4years

Posted on: 4 hours ago

Vacancies: 1 Vacancy

Job Summary

About the Role Were seeking an exceptional AI/ML Engineer who breaks the traditional mold.

This isnt a role for someone who only trains models or lives in Jupyter notebooks.

We need an end-to end product engineer who happens to have deep AI/ML expertisesomeone who can architect scalable systems ship production code own product outcomes and drive technical decisions from conception to deployment.

Youll be responsible for building and scaling AI-powered products that directly impact our users and business.

This means taking models from research to production designing robust APIs optimizing infrastructure collaborating with cross-functional teams and owning the complete product lifecycle.

If youre a builder who thrives on seeing your work in users hands and measures success by product impact rather than model accuracy alone this role is for you.

What Youll Own Product Development & Delivery: Youll own entire AI/ML products from ideation to production.

This includes defining technical architecture making build-vs-buy decisions scoping MVPs and delivering features that solve real user problems.

Youll work closely with product managers and designers but youll drive technical strategy and execution independently. End-to-End ML Systems: Design and implement complete ML pipelines including data ingestion feature engineering model training evaluation deployment and monitoring. Youll build systems that are maintainable scalable and production-readynot just experimental notebooks.

Production Engineering: Write clean tested production-grade code across the stack. Build RESTful APIs implement efficient data processing pipelines optimize model serving infrastructure and ensure systems are reliable performant and cost-effective at scale.

Technical Architecture: Make critical architectural decisions around model selection infrastructure design data flow and system integration. Youll evaluate trade-offs between different approaches prototype solutions and champion best practices across the team.

Cross-Functional Leadership: Collaborate with engineering product design and business teams to translate requirements into technical solutions. Youll advocate for users communicate complex technical concepts clearly and drive alignment on priorities and timelines.

Performance & Optimization: Continuously improve system performance model accuracy latency and resource utilization. Implement monitoring and observability to catch issues early and iterate based on production metrics and user feedback. What Were Looking For

Experience Profile: 4-6 years of software engineering experience with at least 3 years building and deploying AI/ML systems in production environments. Youve shipped real products that users depend on not just research projects or POCs. ML Engineering Excellence: Strong fundamentals in machine learning with hands-on experience across multiple domainsNLP computer vision recommendation systems or time-series forecasting. You understand model selection training strategies evaluation metrics and when to use different architectures.

Proficiency with PyTorch or TensorFlow scikit-learn and modern ML frameworks. Software Engineering Chops: Youre a strong programmer who writes clean maintainable code. Solid proficiency in Python with experience in at least one additional language (Go Java JavaScript or C).

Deep understanding of data structures algorithms design patterns and software architecture principles. Production ML Systems: Proven track record building scalable ML infrastructure including model serving (TensorFlow Serving TorchServe ONNX) feature stores experiment tracking (MLflow Weights & Biases) and CI/CD for ML.

Experience with containerization (Docker Kubernetes) and cloud platforms (AWS GCP or Azure). Full-Stack Capabilities: Ability to build complete features end-to-end. Experience with backend development (FastAPI Flask) API design databases (SQL and NoSQL) caching strategies and basic frontend skills when needed.

Youre comfortable working across the stack. Data Engineering Skills: Strong SQL and data manipulation skills with experience building ETL/ELT pipelines. Proficiency with data processing frameworks (Spark Dask or similar) and working with both structured and unstructured data at scale.

Product Mindset: You think beyond technical implementation to user impact and business outcomes. Experience working closely with product teams translating ambiguous requirements into technical solutions and making pragmatic engineering decisions that balance quality speed and scope.

System Design: Ability to design robust scalable systems considering performance reliability security and cost. Experience with distributed systems microservices architecture and handling high-traffic production environments. Technical Stack Exposure Experience with modern LLM frameworks (LangChain LlamaIndex Haystack) vector databases (Pinecone Weaviate Qdrant) and RAG architectures is highly valued.

Familiarity with model optimization techniques (quantization pruning distillation) and serving optimizations. Understanding of MLOps best practices and tools for model monitoring versioning and governance. What Sets You Apart Youve built AI features that thousands or millions of users interact with daily.

You have strong opinions on engineering practices but remain pragmatic about trade-offs. Youve mentored other engineers and elevated team standards. Youre comfortable with ambiguity and can scope and execute projects with minimal guidance. You stay current with AI/ML advances but know when to use proven approaches versus cutting-edge research. You have experience with A/B testing and experimentation frameworks. Youve dealt with model drift data quality issues and production incidents emerging with better systems and processes.

What Success Looks Like In your first six months youll own at least one significant AI/ML feature from design to deployment improve our ML infrastructure and development velocity establish monitoring and evaluation frameworks for production models and become a go-to technical resource for AI/ML product decisions across the organization.

Were building products that require both deep technical expertise and strong product intuition. If youre excited about the intersection of AI/ML and product engineering and you want to see your work directly impact users while working with cutting-edge technology wed love to hear from you.

Required Skills:

4-6 years of software engineering experience with at least 3 years building and deploying AI/ML systems in production environments. Youve shipped real products that users depend on not just research projects or POCs. ML Engineering Excellence: Strong fundamentals in machine learning with hands-on experience across multiple domainsNLP computer vision recommendation systems or time-series forecasting. You understand model selection training strategies evaluation metrics and when to use different architectures. Proficiency with PyTorch or TensorFlow scikit-learn and modern ML frameworks. Software Engineering Chops: Youre a strong programmer who writes clean maintainable code.