Engineering Manager-AI/ML

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Overall Industry Experience

8 to 12 years

Job Description

We are seeking a highly motivated and experienced ML Manager / Lead Data Scientist to join our growing ML/GenAI team. You will play a key role in designing, developing, and productionalizing ML/GenAI applications by evaluating models, training and/or fine‑tuning them. As a lead, you require a deep understanding of both machine learning algorithms and software architecture. You need to take ownership of projects from conception to deployment, collaborating with engineers and stakeholders to ensure successful project delivery.

What We’re Looking For

• At least 5 years of experience in designing & building ML/AI applications for customers and deploying them into production
• At least 8 years of software engineering experience in building secure, scalable, and performant applications for customers
• At least 2 years of experience leading and mentoring ML/data science teams (4+ team members)
• Experience with document extraction using AI, conversational AI, vision AI, NLP, or GenAI

Responsibilities

• Design, develop, and operationalize existing ML models by fine‑tuning and personalizing them
• Evaluate machine learning models and perform necessary tuning
• Develop prompts that instruct LLMs to generate relevant and accurate responses
• Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation
• Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance
• Lead the end‑to‑end design and architecture of scalable, reliable, and cost‑effective generative AI solutions, including RAG (Retrieval‑Augmented Generation) pipelines, agentic workflows, and model fine‑tuning strategies
• Hands‑on customer experience with RAG solutions or fine‑tuning of LLM models
• Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards, or CRM tools
• Perform end‑to‑end data work: cleaning, exploratory analysis, handling outliers and imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, training, and deployment
• Act as the senior‑most developer, writing clean, high‑quality, and scalable code, including core components for prompt engineering, vector search, data processing, model evaluation, and inference serving
• Proven experience building and deploying machine learning models in production environments for real‑life applications
• Good understanding of natural language processing, computer vision, or other deep learning techniques
• Expertise in Python, NumPy, Pandas, and various ML libraries (e.g., XGBoost, TensorFlow, PyTorch, Scikit‑learn, LangChain)
• Familiarity with Google Cloud or any other cloud platform and its machine learning services
• Excellent communication, collaboration, and problem‑solving skills

Good to Have

• Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent
• Experience working with one or more public cloud platforms – namely GCP, AWS, or Azure
• Experience with AutoML and vision techniques
• Master’s degree in statistics, machine learning, or related fields