Experience required: 5-10 Yrs
Skills: Machine Learning, Python, Generative AI, LLMs, Deep Learning, AI Agents, Hugging Face, MLflow, NumPy, LLM Evaluation, LangGraph, Embeddings, NLP, PyTorch, Vector Databases, AWS, TensorFlow, LangChain, Scikit-learn, Prompt Engineering, MLOps, Git, Pandas, Time Series, RAG, Computer Vision, Fine-tuning

Role & responsibilities

Lead the design, development, deployment, and maintenance of production-grade machine learning systems.
Provide technical leadership to ML Engineers, Data Scientists, and AI Engineers across the ML lifecycle.
Translate business and product requirements into scalable ML solutions and technical architectures.
Develop and productionize models for prediction, classification, recommendation, NLP, computer vision, and Generative AI use cases.
Design and implement robust ML pipelines for data preparation, feature engineering, training, validation, deployment, and monitoring.
Establish and improve MLOps practices, including CI/CD, model versioning, experiment tracking, model serving, and monitoring.
Optimize models and ML infrastructure for accuracy, latency, scalability, reliability, and cost efficiency.
Design scalable model-serving and inference architectures for batch and real-time applications.
Evaluate and integrate LLMs, foundation models, RAG, vector databases, and AI-agent technologies where appropriate.
Collaborate with Data Engineering, Software Engineering, Product, DevOps, and Data Science teams.
Conduct technical design reviews, code reviews, architecture reviews, and establish engineering best practices.
Troubleshoot production ML issues and lead root-cause analysis and resolution.
Define technical roadmaps, estimate engineering effort, prioritize initiatives, and ensure timely delivery.
Mentor engineers and promote best practices in ML engineering, software development, testing, and documentation.
Ensure ML systems comply with requirements for data privacy, security, model governance, fairness, and responsible AI.
Research emerging ML technologies and identify opportunities to improve existing products and platforms.

Preferred candidate profile

5 to 10 years of experience in Machine Learning Engineering, AI Engineering, Data Science, or related technical roles, with demonstrated technical leadership.
Strong hands-on expertise in Python, Machine Learning, Deep Learning, and production ML systems.
Strong proficiency in PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, or equivalent ML frameworks.
Experience with Generative AI, LLMs, RAG, embeddings, vector databases, prompt engineering, fine-tuning, and model evaluation is highly desirable.
Strong understanding of MLOps, including MLflow/Kubeflow, experiment tracking, model versioning, deployment, monitoring, and CI/CD.
Experience deploying ML solutions on AWS, Azure, or GCP.
Proficiency with Docker, Kubernetes, Git, Terraform, APIs, microservices, and cloud infrastructure.
Strong understanding of SQL, data pipelines, feature engineering, feature stores, distributed systems, and system design.
Experience with real-time and batch inference, model serving, model optimization, and production monitoring.
Demonstrated ability to take ML solutions from research/PoC to reliable production systems.
Strong knowledge of software engineering principles, testing, code quality, scalability, and performance optimization.
Experience mentoring engineers and leading cross-functional technical initiatives.
Strong problem-solving, communication, stakeholder management, and technical decision-making skills.
Ability to balance model performance, engineering complexity, infrastructure cost, scalability, and business requirements.
Bachelor's degree in Computer Science, AI/ML, Data Science, Engineering, Mathematics, Statistics, or a related field; Master's degree preferred.
Experience with responsible AI, model governance, security, and data privacy is an advantage.
Role: Engineering Manager
Industry Type: IT Services & Consulting
Department: Engineering - Software & QA
Employment Type: Full Time, Permanent
Role Category: Software Development
Education
UG: B.Tech / B.E. in Computer Science and Engineering (CSE), Artificial Intelligence And Data Science, Artificial Intelligence And Machine Learning