<p><p>We are looking for a skilled and hands-on Machine Learning Engineer with a strong foundation in Python, ML engineering tools, and applied experience in building and managing production-grade ML pipelines.
Youll work on end-to-end ML systems, from data processing and feature engineering to model deployment and monitoring.<br/><br/>This role requires a deep understanding of ML lifecycle, experience with LLMs and RAG pipelines, and the ability to optimize distributed data and compute systems.<br/><br/><b>Key Requirements :</b><br/><br/><b>Core Skills :</b><br/><br/>- Proficient in Python<br/></p><p><br/></p><p>- Experience with at least one cloud platform (GCP preferred but not mandatory)<br/></p><p><br/></p><p>- Strong understanding of the end-to-end ML lifecycle<br/></p><p><br/></p><p>- Experience with ML modeling, evaluation metrics, and model monitoring<br/></p><p><br/></p><p>- Familiar with ML frameworks such as TensorFlow or PyTorch<br/><br/><b>ML Engineering Tools & Infrastructure :</b><br/><br/>- Experience with Docker and managing environments (venv, pip, poetry, etc.)<br/></p><p><br/></p><p>- Exposure to orchestrators like Vertex AI Pipelines, Airflow, etc.<br/></p><p><br/></p><p>- Advanced SQL skills<br/></p><p><br/></p><p>- Familiarity with CI/CD pipelines, deployment methodologies, and infrastructure automation (e.g., Terraform)<br/></p><p><br/></p><p>- Hands-on with distributed computing and tools like Apache Spark, Beam, or Flink<br/><br/><b>Data Engineering :</b><br/><br/>- Strong grasp of data and feature engineering techniques<br/></p><p><br/></p><p>- Understanding of streaming concepts such as windowing, late arrival, and triggers<br/></p><p><br/></p><p>- Experience with designing data architectures and pipeline optimization<br/><br/><b>LLM & RAG :</b><br/><br/>- Exposure to LLM-based workflows : embeddings generation, indexing, Retrieval-Augmented Generation (RAG), agents, etc.<br/></p><p><br/></p><p>- Familiarity with vector databases like Qdrant<br/><br/><b>Education :</b><br/><br/>- B.Tech / B.E. in Computer Science, Data Science, Information Technology, or a related technical field<br/></p><p><br/></p><p>- Equivalent practical experience may also be considered</p><br/></p> (ref:hirist.tech)