Senior Data Science/ML Engineer

About the Position

We are looking for a Senior Data Science/ML Engineer with strong software engineering and code implementation experience to develop enterprise level AI solutions. You should demonstrate strong ownership, proactivity, and communication skills, including the ability to independently investigate issues, propose solutions, identify blockers early, and keep stakeholders informed. This role involves working with generative AI, fine tuning models, and building scalable applications, with a strong focus on measuring, evaluating, optimizing, and continuously improving AI solutions in production. As a Senior Data Science/ML Engineer, you will design, build, and deploy production grade machine learning systems at scale, with a particular emphasis on evaluation frameworks, performance measurement, and optimization of models in production. You will work across the entire ML lifecycle, from research and prototyping to model training, evaluation, optimization, and deployment. This is a highly impactful senior level role where you will influence architecture, roadmaps, and AI/ML best practices across the organization.

Responsibilities

• Define and implement frameworks for measuring, evaluating, and continuously improving AI/ML solutions in production.
• Build AI agent systems and multi step workflows using LangGraph.
• Fine tune encoder based and generative models for production use.
• Develop production ready Python applications with FastAPI or Flask that interact with AI models.
• Design agentic workflows with tool usage, memory management, and state management.
• Deploy, monitor, and optimize ML models in production environments, including evaluation pipelines and performance benchmarking.
• Use AI coding assistants regularly as part of the development workflow.

Requirements

• 5+ years of experience in ML/AI, with strong Python software engineering and hands on development experience.
• Proven experience designing model evaluation frameworks, defining metrics, and developing optimization strategies for production AI systems.
• Experience fine tuning encoder models such as BERT and RoBERTa, as well as working with large language models.
• Experience with LangGraph, AI agents, and multi step reasoning systems.
• Proficiency in building production APIs and web applications using FastAPI, Flask, or Django.
• Experience with PyTorch or TensorFlow, Hugging Face, vector databases, and RAG architectures.
• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization technologies such as Docker.
• Strong understanding of MLOps practices, production ML systems, model monitoring, and observability.

Nice to Have

• Master's degree or PhD in Computer Science, Machine Learning, or a related field.
• Experience with multi agent systems and agent communication frameworks.
• Knowledge of advanced prompting techniques and reasoning patterns.
• Publications or open source contributions in AI/ML.
• Experience scaling AI systems for high traffic production environments.