Senior AI/ML Engineer
New
Based in IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6–10 years
- Required Skills
- AWSDockerPythonSQLNumpyPyTorchPandasTensorflowscikit-learnMLOps
Requirements
- 6–10 years of professional experience in AI, Machine Learning, or related software engineering roles.
- Strong programming skills in Python, including experience with NumPy, Pandas, and SQL.
- Hands-on expertise with machine learning and deep learning frameworks such as scikit-learn, PyTorch, and TensorFlow.
- Experience implementing MLOps practices, including Docker, CI/CD pipelines, and production deployment workflows.
- Proficiency with cloud platforms such as AWS and/or Azure.
- Solid understanding of modern AI application development, including Retrieval-Augmented Generation (RAG), embeddings, vector databases, NLP, transformer models, model evaluation, monitoring, and API-based model serving.
- Demonstrated experience in solution architecture, technical leadership, stakeholder communication, and mentoring engineering teams.
- Excellent analytical, problem-solving, communication, and collaboration skills with the ability to work effectively in distributed teams.
Responsibilities
- Lead the design, architecture, and end-to-end delivery of enterprise-scale AI and machine learning solutions, including advanced agentic AI applications.
- Define technical solutions, provide project estimations, and contribute to delivery planning to ensure successful execution.
- Collaborate closely with cross-functional teams and stakeholders in Agile/SCRUM environments, translating business requirements into scalable AI solutions.
- Build, deploy, and maintain production-ready machine learning systems using modern MLOps practices, cloud technologies, and API-based model serving.
- Mentor and support junior and mid-level engineers, promoting technical excellence, best practices, and high-quality software delivery.
- Drive technical discussions with stakeholders, validate solution approaches, and ensure alignment with project objectives.
- Champion responsible AI principles by implementing monitoring, evaluation, governance, and compliance throughout the AI lifecycle.
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