Senior Machine Learning Engineer - Hybrid

Lead the design, development, and scale of our AI Worker platform — a multimodal, agentic system handling voice, vision, and language in real time — while mentoring junior engineers and collaborating across teams.

• Company details
• GoCommotion builds AI Workers for the future of customer experience (CX). We create intelligent agents that engage across channels, listen to asynchronous events, and continuously improve.
• Website: https://www.gocommotion.com/
• Requirements
• Bachelor’s or Master’s in Computer Science, AI/ML, or related field
• Expert in Python; strong grasp of data structures, algorithms, OS, networking fundamentals
• Competitive coding / problem-solving track record is a plus
• 3+ years’ experience in production ML systems
• Deep knowledge of LLMs (architecture, fine‑tuning, LoRA / PEFT / instruction tuning)
• Experience in multimodal ML (text, vision, voice)
• Hands‑on with Voice AI: ASR, TTS, speech embeddings, latency optimization
• Experience building RAG pipelines (embed models, vector DBs, hybrid retrieval)
• Strong foundation in reinforcement learning (RLHF, policy optimization, continual learning)
• Proficient with PyTorch, TensorFlow, scikit‑learn
• Familiarity with vLLM, HuggingFace, Agno, LangFlow, CrewAI, LoRA frameworks
• Experience with vector stores (Pinecone, Weaviate, FAISS, QDrant) and orchestration
• Experience in distributed training, large‑scale pipelines, inference latency optimization
• Experience deploying ML in cloud (AWS / GCP / Azure), containers, Kubernetes, CI/CD
• Ownership mindset, ability to mentor, high resilience, thrive in startup environment

• Currently employed at a product-based organisation

• Responsibilities
• Build AI systems powering AI Workers — agentic, persistent, multimodal across voice, text, image
• Lead full ML lifecycle: data pipelines, architecture, training, deployment, monitoring
• Design speech‑to‑speech models (without text intermediary) for low‑latency voice interaction
• Drive LLM fine‑tuning and adaptation strategies (LoRA, PEFT, instruction tuning)
• Architect and optimize RAG pipelines for live grounding of LLMs
• Advance multimodal systems integrating language, vision, and speech
• Apply reinforcement learning (online/offline) for continuous improvement
• Collaborate with infra and systems engineers for GPU clusters, cloud, edge integration
• Translate research ideas into production innovations
• Mentor junior ML engineers, define best practices, shape technical roadmap
• Job Details
• Location: Hybrid — Mumbai, Bengaluru, Chennai, India
• Interview process
• Screening / HR round
• Technical round(s) — coding, system design, ML case studies
• ML / research deep dive
• Final / leadership round
• Important Note
• ClanX is a recruitment partner, helping GoCommotion hire the Senior Machine Learning Engineer.