Senior AI/ML Engineer

Job Title: Senior AI/ML Engineer

Location: Hyderabad, India 5 days a week onsite

Company Overview:

Circuitry.ai is at the forefront of artificial intelligence innovation, specializing in developing AI-driven software solutions that transform how industries operate. By harnessing the power of machine learning, predictive modelling, and generative AI , we help organizations unlock deep insights, drive automation, and make data-informed decisions at scale.

Our AI solutions have been applied across a variety of domains, including automotive OEM, warranty analytics, manufacturing intelligence , and customer experience optimization. We are passionate about building AI systems that are not only powerful but also transparent, explainable, and aligned with real-world business outcomes.

Role Overview:

As a Senior AI/ML Engineer , you will be responsible for designing, developing, and deploying end-to-end machine learning solutions that are explainable, scalable, and impactful. You will work closely with AI Engineers, data engineers, and managers to translate business requirements into actionable AI/ML models and deploy them over cloud infrastructure.

This role is ideal for someone who thrives on solving complex problems, enjoys exploring emerging technologies like GenAI frameworks , and can communicate insights effectively to both technical and business stakeholders.

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: Bachelors or Masters 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.