- Company Name
- ViewIn Advisory
- Job Title
- Machine Learning Engineer (open for 2026 PhD New Graduates)
- Job Description
-
**Job Title:** Machine Learning Engineer (LLM / ML Infrastructure)
**Role Summary:**
Design, build, and maintain scalable machine learning infrastructure and deployment pipelines for large language models. Develop SDKs and tools that empower developers to create and optimize AI agents. Collaborate directly with customers to implement and refine AI solutions, improving model performance, reliability, and scalability in a fast‑moving startup environment.
**Expectations:**
- Deliver production‑ready ML infrastructure and deployment systems for large language models.
- Create SDKs and APIs that simplify AI agent development for external users.
- Partner with customers to launch and tune AI solutions in real‑world settings.
- Continuously optimize model performance, reliability, and scalability.
**Key Responsibilities:**
- Design and implement end‑to‑end ML pipelines (data ingestion, training, validation, deployment).
- Build robust, scalable infrastructure (batch and streaming) for LLM training and inference.
- Develop SDKs, developer tools, and APIs that enable easy integration of AI agents.
- Work with clients to deploy models, diagnose issues, and apply performance boosts.
- Monitor, log, and tune model and system metrics; implement alerts and automated remediation.
- Stay current on LLM research and incorporate cutting‑edge techniques into production.
**Required Skills:**
- PhD in Machine Learning, AI, NLP, or closely related field.
- Proficiency in Python and at least one major ML framework (PyTorch, TensorFlow, or JAX).
- Deep understanding of large language models, NLP, or deep learning paradigms.
- Hands‑on experience building ML infrastructure, training pipelines, and deployment systems.
- Strong coding and software engineering practices (version control, testing, CI/CD).
- Excellent communication and client‑facing collaboration abilities.
- Ability to work independently and in a fast‑paced startup environment.
**Required Education & Certifications:**
- PhD in Machine Learning, Artificial Intelligence, Natural Language Processing, or an equivalent technical discipline.
- (Optional) Publications in top conferences such as NeurIPS, ICML, ICLR, ACL, or EMNLP.
- (Optional) Demonstrated experience building ML platforms, APIs, or SDKs.
Mountain view, United states
Hybrid
12-02-2026