Machine Learning Engineer - NLP/LLM

As an ML EngineerI, you will play a pivotal role in leading and mentoring a team of talented ML engineers and researchers.

You will shape the technical vision for our core AI components, drive execution of our ambitious Voice AI roadmap, and deliver high-impact ML solutions.

This role demands a strong balance of deep technical expertise, leadership skills, and innovation mindset in the AI space.

Key Responsibilities :

- Provide technical leadership and direction for major ML initiatives, including custom ASR/TTS, V2V development (with SSMs like Mamba, Hamba), Agentic RAG systems, and LLM orchestration.

- Foster a culture of growth, learning, and high performance within the ML team.

- Oversee the end-to-end ML project lifecycle: ideation, research, development, deployment (with MLOps), and iteration.

- Drive architectural decisions to ensure scalability, reliability, and real-time performance for voice AI applications.

- Collaborate with product, engineering, and business stakeholders to define requirements, priorities, and deliverables.

- Stay updated on advancements in speech AI, NLP, and LLMs; champion their adoption where relevant.

- Design and implement research & development roadmaps for next-generation Voice AI, including multilingual and V2V capabilities.

- Contribute to hiring and building a world-class ML team.

Requirements :

- Bachelors Degree in Computer Science or related field.

- 4+ years of hands-on experience in machine learning, with proven leadership or senior technical contributions.

- Demonstrated success in delivering complex ML projects into production.

- Expertise in at least one domain: ASR, TTS, NLP, Dialogue Systems, LLMs, or RAG.

- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.

- Strong understanding of ML system design, evaluation, and MLOps principles.

- Experience in leading, mentoring, and guiding technical teams.

- Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications :

- Masters or PhD in Computer Science, AI, or related fields.

- Hands-on work with State Space Models (SSMs) and advanced sequence modeling.

- Experience deploying real-time, low-latency ML systems (e.

, Triton, Nvidia Riva, SGLang, vLLM).

- Familiarity with cloud platforms (AWS, GCP, Azure) and ML services.

- Contributions to ML research or open-source projects.

- Experience in developing multilingual AI solutions