What we're looking for:

At least 5 years of experience in designing & building ML/AI applications for customer 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 Gen AI
Design, develop, and operationalize existing ML models by fine tuning, personalizing it
Evaluate machine learning models and perform necessary tuning
Develop prompts that instruct LLM 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. This includes designing RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and model fine-tuning strategies
Hands on customer experience with RAG solution or fine tuning of LLM model
Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools
Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment
Act as the senior-most developer, writing clean, high-quality, and scalable code. This includes building 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 of 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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Engineering Manager-AI/ML