Machine Learning Engineer

About Us

Skit.ai is the pioneer Conversational AI company transforming collections with omnichannel GenAI-powered assistants. Skit.ai's Collection Orchestration Platform, the world's first solution, streamlines collection conversations by syncing channels and accounts. Skit.ai's Large Collection Model (LCM), a collection LLM, powers the strategy engine to optimize interactions, enhance customer experiences, and boost bottom lines for enterprises. Skit.ai has received several awards and recognitions, including the BIG AI Excellence Award 2024, Stevie Gold Winner 2023 for Most Innovative Company by The International Business Awards, and Disruptive Technology of the Year 2022 by CCW. Skit.ai is headquartered in New York City, NY. Visit https://skit.ai/

Job Title

: Machine Learning Engineer

Location

: Bangalore (100% onsite)

Areas Of Technical Work

• LLM-based Agentic Systems for autonomous workflow execution
• Evaluation, Monitoring, Observability, and MLOps for production-grade AI
• LLM-driven Multilingual Language Understanding and Dialogue Management
• Decision Modeling and Optimization for agent interactions
• ML Systems Design and Infrastructure
  

Responsibilities

• Design, build, and optimize ML models powering our AI agents and automation systems
• Contribute to the development of scalable ML pipelines and frameworks
• Collaborate with product managers and engineers to deliver ML-powered features
• Implement robust monitoring, evaluation, and retraining workflows for deployed models
• Research and experiment with state-of-the-art LLMs and ML techniques
• Participate in design discussions, model reviews, and performance evaluations
  

Requirements

• 4+ years of hands-on experience in Machine Learning or Applied AI
• Strong understanding of ML fundamentals (probability, statistics, algorithms)
• Practical experience working with LLMs, NLP, or generative AI systems
• Familiarity with MLOps tools and practices (model deployment, evaluation, monitoring)
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Hugging Face, etc.)
• Experience with cloud platforms (AWS, GCP, Azure) and containerized environments
• Strong problem-solving and analytical skills
• (Preferred) Contributions to open-source projects, blogs, or Git portfolios demonstrating relevant work.