Data Engineer

Sr. Machine Learning Engineer

About the Role 

We are looking for a Senior Machine Learning Engineer to join the Data Science team at 6sense. This role is ideal for someone who combines strong data science fundamentals with deep expertise in building applied machine learning, NLP, and modern GenAI systems. 

You will work on building scalable AI-powered products and intelligent systems that directly impact customer experience and business outcomes. The ideal candidate is technically strong, product-oriented, and capable of thinking end-to-end — from problem framing and experimentation to productionization, monitoring, and long-term evolution of AI systems.

What You’ll Do 

• Design, build, and deploy production-grade ML and AI systems powering core product capabilities 
• Develop and optimize NLP and transformer-based solutions for enterprise-scale use cases 
• Build agentic AI workflows using frameworks such as LangGraph and LangChain 
• Work across the full ML lifecycle including data exploration, feature engineering, model development, evaluation, deployment, and monitoring 
• Apply statistical and machine learning techniques to solve ranking, recommendation, prediction, classification, and optimization problems 
• Partner closely with Product, Engineering, and Data Analytics teams to translate ambiguous business problems into scalable AI solutions 
• Drive end-to-end ownership across experimentation, evaluation, deployment, monitoring, and iteration 
• Improve reliability, latency, scalability, and observability of ML systems in production 
• Contribute to architectural decisions and help define best practices for AI-native application development 
• Mentor junior engineers and contribute to raising the technical bar across the team.

What We’re Looking For 

Required Qualifications 

• 5+ years of experience in building and deploying machine learning systems in production environments 
• Strong foundation in machine learning, statistics, and applied data science 
• Experience with supervised and unsupervised learning techniques, recommendation systems, ranking models, and predictive modeling 
• Strong experience with NLP, transformer architectures, embeddings, encoders-decoder models, and retrieval-based systems 
• Hands-on experience with LLM application frameworks such as LangGraph, LangChain, Amazon Bedrock 
• Strong programming skills in Python and experience with modern ML/AI tooling ecosystems 
• Experience building scalable distributed systems and production ML pipelines in Databricks and AWS ecosystem  
• Strong understanding of data quality, feature engineering, and model operationalization 
• Ability to independently drive ambiguous problems from concept to production 
• Strong product mindset with the ability to think holistically about user experience, business impact, and system design 

Preferred Qualifications 

• Experience building agentic AI systems and multi-agent workflows 
• Familiarity with RAG architectures, vector databases, and prompt engineering 
• Experience with deep learning frameworks such as PyTorch or TensorFlow 
• Experience in B2B SaaS or customer-facing AI products 

Experience Level

Senior Level