Job Details

Applied Machine Learning Scientist

Location: Hybrid (Chicago preferred) or Remote (US)

Hiring via Reach Velocity | Deep Tech & AI Talent Partners

We're working with a global powerhouse in industrial tech that's investing heavily in applied AI to transform content generation, classification, and optimization across its product and marketing platforms.

They're building intelligent systems that power how millions of products are merchandised, categorized, and described - and they need an Applied Machine Learning Scientist to help them go from traditional content management to LLM-driven automation and agentic content systems.

What You'll Be Doing

• Build and optimize GenAI pipelines for rich content management using LLMs, VLMs, RAG, vector search, and agentic frameworks.
• Own the end-to-end lifecycle: from training and fine-tuning to deployment and scaling across the company's digital platforms.
• Work with deep learning frameworks like PyTorch, TensorFlow, Hugging Face to implement and refine models.
• Collaborate with a cross-functional ML team to drive experimentation, testing, and production deployment of new models.
• Utilize and automate workflows using tools like Airflow, Docker, Kubernetes, Sagemaker, Databricks.
• Stay plugged into the latest developments in LLMs, prompt engineering, and agent-based systems - and bring them to life in production.

What You'll Need

• Advanced degree (PhD or Master's) in Applied Math, Physics, Engineering, CS, or related - or a Bachelor's + 2 years of experience.
• Proven experience working with GenAI, LLMs, and VLMs in real-world environments.
• Hands-on experience with model training, fine-tuning, validation, and deployment.
• Solid grounding in Python and ML tooling across the modern stack (HuggingFace, PyTorch, etc.).
• Strong communication skills - this is a collaborative role that touches marketing, engineering, and data.

Bonus Points For

• Familiarity with LangChain, LlamaIndex, Autogen, or Crew.ai
• Model quantization and experience with Triton Inference Server
• Production experience in cloud environments (AWS, Docker, K8s)

Compensation & Benefits

Base Salary: $110,500 - $184,100 (location-adjusted and experience-dependent)

Benefits (Start Day One):

• Medical, dental, vision, and life insurance
• 18 days PTO + 6 company holidays
• 6% 401(k) company contribution (no match required)
• Parental leave up to 14 weeks
• Therapy sessions, tuition support, student loan tools, and more

Note: This role is not eligible for OPT sponsorship now or in the future.