ML Engineer

gofers

Bengaluru, India 5 Years Exp Posted 42d ago

End-to-End ML Development: Design, train, fine-tune, and operationalize robust ML models for real-world customer applications.
GenAI & LLM Implementation: Develop and optimize production-grade Retrieval-Augmented Generation (RAG) systems. Design, evaluate, and iteratively modify prompts to maximize LLM response accuracy.
Data & Feature Engineering: Collaborate with teams to analyze, clean, and preprocess datasets (handling outliers, imbalances, and distributions) and transform raw data into high-quality features.
Production & MLOps: Build and deploy scalable ML pipelines on GCP. Implement robust monitoring strategies to track model performance, identify data drift, and resolve issues in production environments.
Collaboration & Ownership: Act as a senior member on customer-facing projects, translating client needs into secure, performant, and scalable architectures. What We Are Looking For (Requirements)

Requirements

Experience: ○ Minimum 5 years of core Software Engineering experience building secure, scalable, and performant applications. ○ Minimum 3 years of hands-on experience specifically designing, building, and deploying ML applications in production.
Experience integrating ML pipelines with data processing pipelines.

Technical Domain Expertise: ○ Strong foundational knowledge of Natural Language Processing (NLP), Computer Vision, or other Deep Learning techniques. ○ Proven experience building and deploying RAG (Retrieval-Augmented Generation) architectures and engineering prompts for LLMs.
Tools & Frameworks: ○ Expertise in Python and standard data science libraries (NumPy, Pandas, Scikit-learn). ○ Deep familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost) and GenAI orchestration tools (LangChain or similar).
Cloud Infrastructure: Hands-on experience building pipelines on cloud platforms, specifically Google Cloud Platform (GCP) and its machine learning suite (Vertex AI, BigQuery, etc.).
Core Skills: Exceptional problem-solving abilities combined with strong communication and collaboration skills for customer-facing environments. Good to Have (Preferred Qualifications)
- Certificates: Google Cloud Certified Professional Machine Learning Engineer, Google Cloud Generative AI Engineer, or TensorFlow Certified Developer certifications.