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Senior Machine Learning Engineer – Drive AI research, develop large language models, mentor teams at Vanguard’s Hyderabad office.
Lead cutting‑edge AI projects, publish research, and transform prototypes into production solutions.
About Vanguard
Founded in 1975, Vanguard is one of the world's leading investment management companies. The firm offers investments, advice, and retirement services to tens of millions of individual investors around the globe—directly, through workplace plans, and through financial intermediaries.
Vanguard’s India Office
Vanguard’s office in India is a significant milestone in our global expansion. We are committed to establishing an enduring technology center in Hyderabad, Telangana and are excited to be adding talent who will focus on Artificial Intelligence (AI), mobile, and cloud-based technologies that drive our business outcomes and deliver a world‑class experience for our clients.
Role Summary
Push the boundaries of AI innovation while contributing to impactful research and guiding the next generation of publications. We are seeking a Senior Research Engineer to join our dynamic AI research team. In this role, you will work on cutting edge AI technologies, contribute to the development of transformative solutions, and lead research initiatives that result in high impact publications. This role is perfect for someone passionate about applying advanced AI concepts to solve real‑world challenges, publishing their work in top‑tier venues, and mentoring others in the pursuit of groundbreaking research. You’ll collaborate with scientists, engineers, and cross‑functional teams to deliver innovative solutions while contributing to the broader AI research community.
Responsibilities
- Conduct advanced research in AI domains, such as Generative AI, Agentic AI, Cognitive AI architectures, call transcription, and large language models; Drive the development of new algorithms, models and techniques that push the boundaries of AI technology.
- Work closely with engineering teams to transition research findings into scalable, production‑ready solutions; Develop prototypes and proof of concept systems that demonstrate the applicability of research findings to business problems.
- Publish research in top‑tier AI conferences and journals (e.g., NeurIPS, ICML, CVPR, ACL); Present findings at conferences, workshops, and internal forums to showcase advancements and foster knowledge sharing.
- Mentor junior scientists and engineers in conducting high‑quality research and writing impactful publications; Provide technical guidance and support to ensure research aligns with both academic and business goals.
- Partner with cross‑functional teams to align research priorities with business needs; Work closely with product and engineering teams to design AI solutions that are both innovative and practical.
- Ensure all research and solutions adhere to responsible AI principles, prioritizing safety.
Qualifications and Skills
- Minimum 8‑10+ years of experience in machine learning engineering or data science roles
- Advanced degree (Post Doctorate or PhD or master’s in computer science, AI, Data Science or related field).
- Minimum 5+ years of relevant work experience.
- Deep understanding of cutting‑edge AI research topics, such as multi‑agent systems, generative models, or cognitive architectures
- Familiarity with Responsible AI practices and frameworks.
- Consistent publication record in top tier conferences and journals is a plus.
Must Have Skills
- Strong grounding in modern deep learning: transformer architectures, attention mechanisms, training/fine‑tuning dynamics.
- Expert‑level Python and at least one DL framework (PyTorch strongly preferred).
- Hands‑on experience fine‑tuning and adapting LLMs: SFT, LoRA/PEFT, RLHF/DPO, instruction tuning.
- Prompt engineering and production model/LLM monitoring: tracking quality, latency, cost, and failure modes of deployed models. For LLM/agentic systems this means trace‑level visibility into multi‑step chains (which tool call failed, where a reasoning loop went wrong), not just request/response logging.
- Evaluation in production: online evals, regression detection, etc.
- Retrieval‑augmented generation (RAG) and agentic frameworks (tool use, planning, multi‑agent orchestration)
- MLOps tooling: experiment tracking (W&B/MLflow), model serving (vLLM, TGI), containerization, LLM observability tooling (LangSmith, Langfuse, etc.)
- Demonstrated record of taking research from prototype to deployed system.
- Experience with distributed/multi‑GPU training and the practical realities of scaling (DeepSpeed, FSDP, or equivalent).
Nice‑to‑Have
- Cognitive architectures / world models.
- Responsible AI depth: red teaming, evals for safety, interpretability, constitutional methods.
- Cross‑domain ML: multimodal, or RL beyond RLHF.
- Mentorship/tech‑lead experience.
Location
This role is based in Hyderabad, Telangana at Vanguard’s India office. Only qualified external applicants will be considered.
Our mission
Vanguard adheres to a simple purpose: To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.
Our commitment to you
Vanguard takes the same long‑term view of your success—at work and in life—with Benefits and Rewards packages that reflect what you care about, throughout all the phases and stages of your life. Our Total Rewards programs provide you and your loved ones with wellness support for key areas in your life:
Financial wellness
We're committed to enabling your financial success and provide competitive offers and programs.
Physical wellness
We're committed to providing benefits that support your physical health and wellness.
Personal wellness
We're committed to providing resources that help support the full scope of your life.
How we work
Vanguard has implemented a hybrid working model for most of our employees (crew members), designed to capture the benefits of enhanced flexibility while enabling in‑person learning, collaboration, and connection. We believe our mission‑driven and highly collaborative culture is a critical enabler to support long‑term client outcomes and enrich the employee experience.