Senior AI/ML Engineer

Job Title:

Location:

Company Overview:

Circuitry.ai

automotive OEM, warranty analytics, manufacturing intelligence

Role Overview:

Senior AI/ML Engineer

GenAI frameworks

Key Responsibilities:

Model Development & Explainability

• Design, develop, and deploy predictive and prescriptive ML models using state-of-the-art algorithms and tools.
• Implement explainable AI (XAI) frameworks to ensure transparency, interpretability, and trust in model predictions.
• Evaluate model fairness, bias, drift, and performance over time; recommend retraining or improvements.

End-to-End ML Engineering

• Own the full lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring.
• Operationalize models using CI/CD pipelines on cloud platforms (AWS, GCP, or Azure).
• Collaborate with data engineers to design scalable data pipelines for model input/output.

GenAI & Emerging Tech Integration

• Stay up to date with the latest advancements in

  Generative AI, LLMs, vector databases, and embedding-based retrieval systems

  .
• Experiment with integrating GenAI capabilities (e.g., summarization, reasoning, anomaly explanation) into predictive workflows.
• Evaluate new frameworks (LangChain, LlamaIndex, Hugging Face, OpenAI APIs) for business relevance.

Data Analysis & Research

• Conduct in-depth exploratory data analysis to uncover trends, anomalies, and actionable insights.
• Document experimental results, methodologies, and findings comprehensively for cross-functional consumption.
• Contribute to internal knowledge sharing and best practices in model governance and reproducibility.

Collaboration & Mentorship

• Mentor junior data scientists and engineers, providing technical guidance on best practices in ML development and deployment.
• Work closely with Product Managers, TPMs, and business stakeholders to align model outputs with business objectives.
• Clearly communicate technical results, model limitations, and recommendations to non-technical audiences.

Qualifications:

Required Skills:

• Education:

  Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field.

• Experience:

  Minimum 4+ years of exclusive experience building and deploying ML/AI models in production environments.

• Programming:

  Expert in Python; proficient with key ML/data libraries (pandas, scikit-learn, TensorFlow/PyTorch, SHAP/LIME).

• Explainability:

  Strong understanding of model interpretability techniques, fairness, and trust frameworks.

• Cloud & Deployment:

  Hands-on with ML model deployment and MLOps using AWS Sagemaker, GCP Vertex AI, or Azure ML.

• Version Control & CI/CD:

  Familiarity with Git, Docker, and CI/CD tools for model lifecycle management.

• Communication:

  Excellent documentation, analytical reasoning, and stakeholder management skills.

Preferred / Nice to Have:

• Experience working in

  automotive OEM, warranty, or manufacturing domains

  .
• Exposure to

  Generative AI tools and frameworks

  (OpenAI APIs, Hugging Face Transformers, LangChain, etc.).
• Knowledge of

  time series forecasting

  ,

  anomaly detection

  , or

  failure prediction models

  .
• Experience integrating models with cloud-based applications via REST APIs or microservices.