AI/ML Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and deploy AI/ML features encompassing data preparation, model training or fine-tuning, evaluation, deployment, and monitoring.

• Take ownership of features from start to finish and refine them based on feedback from production.

• Construct RAG pipelines and collaborate with LLM APIs and open-source models.

• Create dependable prompts and enhance agentic workflows.

• Develop data pipelines, labeling workflows, and evaluation frameworks.

• Utilize AI to address challenges in manufacturing, supply chain, and physical operations.

• Engage in computer vision tasks related to quality inspection, predictive maintenance, and sensor data applications.

• Tackle problems in demand forecasting, inventory planning, supplier risk management, and logistics.

• Partner with teams in Vehicle Engineering, Manufacturing, and Operations.

• Convert organizational needs into AI systems that yield quantifiable results.

• Report directly to the Distinguished Engineer of Generative AI.

⛳️ Requirements

• A PhD in a relevant field is highly advantageous for early-career candidates, or at least 3 years of professional or research experience in ML systems for candidates without a PhD.

• Proven capability to develop an end-to-end project, thesis, or production system.

• Fundamental understanding of ML concepts: model training, loss functions, evaluation metrics, overfitting, and regularization.

• Hands-on experience with supervised learning, NLP, computer vision, and time-series modeling.

• Familiarity with LLM APIs such as OpenAI, Anthropic, or Gemini.

• Basic knowledge of RAG, embeddings, or retrieval systems.

• Strong ability to rigorously evaluate model quality.

• Proficiency in Python, particularly with PyTorch or JAX, Hugging Face, pandas, and scikit-learn.

• Capability to write high-quality production code.

• Working familiarity with AWS, GCP, or Azure.

• Experience with version control, experiment tracking, and basic MLOps practices.

• A BS degree is required.

• An MS or PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering, Mechanical Engineering, Industrial Engineering, or a related field is preferred.

• Ability to articulate technical decisions to non-technical stakeholders.

• Willingness to engage directly with stakeholders.

• Background or genuine interest in Mechanical Engineering, Electrical Engineering, Robotics, Industrial Engineering, or a related physical discipline is valued.

• Experience with computer vision, sensor data, or real-time systems is valued.

• Familiarity with supply chain, logistics, or operations research problems is valued.

• Experience in simulation environments or working with physical hardware in a research or lab setting is valued.

🏝️ Benefits

• Medical insurance

• Dental insurance

• Vision insurance

• Life insurance

• Disability insurance

• Vacation

• 401k

• Eligibility for equity program

• Eligibility for discretionary annual incentive program

• Reasonable accommodations for qualified individuals with disabilities