Own the full lifecycle of AI/ML solutions—from problem framing and system design through training, evaluation, deployment, and iteration in production.
Translate ambiguous business problems into scalable AI architectures and agent behaviors.
Drive technical decisions around model selection, data strategy, and evaluation frameworks.
Design and implement production-grade agentic systems, including reasoning, planning, orchestration, memory, and tool-use.
Ensure systems are reliable, observable, and perform at scale.
Improve system reliability through metrics, alerts, drift detection, and performance monitoring.
Evaluate and integrate emerging techniques (e.g., LLMs, RAG, knowledge-augmented systems) with a strong focus on production readiness and ROI.
Help build intelligent data products such as recommendation engines, personalization, categorization, search ranking, forecasting, and fraud detection.
Collaborate across teams and work closely with product managers, designers, and software engineers to build AI agents that solve real world problems.
Requirements
7+ years of experience in applied ML / AI engineering, with a strong track record of shipping and operating production AI systems in high-growth startups.
Experience in product-focused environments building end to end SaaS products, where ownership and execution matter.
Demonstrated ability to work in ambiguous, 0→1 problem spaces.
Proven experience building and deploying ML models for real-world use cases (e.g., recommendations, search, NLP, categorization).
MLOps & Infrastructure: Deployment, monitoring, CI/CD, ML pipelines, containerization, and cloud infrastructure.
Full-stack ML expertise across: Data Engineering (feature engineering/ store, distributed data processing).
Strong programming skills using Spark, Python, TensorFlow/PyTorch, MLFlow, Airflow, Docker, Kubernetes, etc.
Experience with Knowledge graphs is a big plus.
Bachelor’s or Master’s degree in Computer Science, Engineering, Econometrics/ Statistics, or related field—or equivalent practical experience.
Passion for building usable, scalable products — not just research or models.
Clear communicator with a collaborative mindset, eager to grow and contribute within a small, fast-paced team.