Senior Machine Learning Engineer

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: Mumbai, Bengaluru, Chennai, India (Hybrid - Optional incase of onsite)

Interview process

• Screening / HR round

• Technical round(s) — coding, system design, ML case studies

• ML / research deep dive

• Final / leadership round