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.