Machine Learning Engineer

Machine Learning Engineer

Experience:

Work Location:

Job Summary:

We are looking for a Machine Learning Engineer with 2–4 years of experience in building and deploying ML-driven solutions, including ML and GenAI-based systems. The role involves working across the full ML lifecycle, from data preparation and model development to deployment, monitoring, and continuous improvement in production environments.

Key Responsibilities:

• Build, train, and optimize machine learning and GenAI models for production use cases.
• Work with large-scale structured and unstructured datasets (text, images, embeddings, tabular data).
• Implement feature engineering, data preprocessing, and model evaluation pipelines.
• Develop and deploy ML/GenAI models. Integrate ML solutions with backend systems and applications.
• Work with embedding models, vector databases, or retrieval-based ML systems where applicable. Monitor model performance, latency, and quality in production.
• Collaborate closely with data engineers, backend engineers, and product teams.
• Document model behavior, assumptions, and deployment workflows.

Required Skills & Qualifications:

• 2+ years of hands-on experience as a Machine Learning Engineer.
• Solid understanding of machine learning concepts and algorithms.
• Experience with frameworks such as PyTorch, TensorFlow, scikit-learn, Langchain, LangGraph etc.
• Familiarity with NLP, embeddings, or deep learning–based models.
• Hands-on experience with GenAI systems (LLMs, prompt engineering, RAG pipelines, fine tuning)
• Experience with data processing using Pandas, NumPy, and SQL.
• Understanding of model deployment, inference, and performance optimization.
• Experience using Git and working in Linux-based environments.
• Experience with cloud platforms such as AWS / GCP / Azure.
• Experience with Docker and containerized deployments.
• Strong communication skills with the ability to explain ML/GenAI concepts clearly to both technical and non-technical stakeholders.

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