Machine Learning Engineer

Work Location: Bengaluru

Immediate Hiring Night Shift only - Customer support time - 8 am to 5 pm EST.

Min ML Experience is 3 years required & Min Software Engineering experience is 5 years required

If you are shortlisted, you must complete an AI interview within 24 hours. Job Overview We are seeking a highly motivated and

experienced ML Engineer to join our growing ML/GenAI team . In this role, you will play a key part in designing, developing, fine-tuning, and productionalizing both classical ML applications and cutting-edge GenAI solutions. As a senior member of the team, you will take ownership of projects and collaborate with engineers and Customers to ensure successful project delivery.

Key Responsibilities

• 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). D

eep 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.