Senior Machine Learning Engineer - PyTorch/Tensorflow

Description :

Key Responsibilities :

- Design, build, and deploy machine learning models using pandas, scikit-learn, mlflow, gensim, nltk, and TensorFlow/PyTorch.

- Conduct feature engineering, model training, validation, optimization, and experimentation.

- Ensure reproducibility through effective model tracking, versioning, and documentation.

- Build and maintain production-ready ML pipelines on cloud platforms such as AWS, Azure, or GCP.

- Implement and maintain monitoring frameworks including model drift detection, data quality checks, and performance dashboards.

- Architect scalable ML systems that align with enterprise-grade reliability, security, and compliance standards.

- Work with advanced NLP techniques including embeddings, vector search, and semantic retrieval using vector databases.

- Fine-tune and deploy large language models (LLMs) using frameworks like HuggingFace, LangChain, and OpenAI.

- Develop custom conversational systems, text generation pipelines, and NLP-driven applications.

- Collaborate closely with data engineering, product teams, and business stakeholders to translate requirements into ML solutions.

- Communicate complex ML concepts to both technical and non-technical audiences.

- Guide junior team members and contribute to best practices, design reviews, and technical standards.

- Stay updated with the latest developments in ML, deep learning, NLP, and MLOps.

- Evaluate emerging tools, frameworks, and architectures to enhance organizational capabilities.

- Drive innovation and value creation through machine learning and AI initiatives.

Required Qualifications & Skills :

- 6+ years of hands-on experience in data science and machine learning.

- Expertise with ML and data science libraries : pandas, scikit-learn, mlflow, nltk, gensim, TensorFlow/PyTorch.

- Experience deploying ML models on AWS, Azure, or GCP, including monitoring and drift detection.

- Strong background in NLP and LLMs : vector databases, fine-tuning, and deployment.

- Experience with HuggingFace, LangChain, OpenAI, or similar frameworks.

- Graduate degree in a quantitative field (Computer Science, Engineering, Statistics, Operations Research) or equivalent practical experience.

- Excellent communication and teaching capabilities for cross-functional collaboration.

- Passion for problem-solving, innovation, and continuous learning.

Preferred Skills :

- Experience using Apache Spark for large-scale distributed data processing.

- Hands-on experience with the Databricks platform, including ML and data engineering workflows.

- Familiarity with CI/CD pipelines, containerization (Docker), and orchestration tools (Kubernetes).