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Senior AI / ML Engineer

Senior AI / ML Engineer

Circuitry.aiguwahati, assam, in
18 hours ago
Job description

Job Title : Senior AI / ML Engineer

Location : Hyderabad, India – Hybrid Remote (3 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 : 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.
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