We are seeking a highly skilled Machine Learning Engineer to design, build, and deploy production‑ready AI and GenAI solutions at scale. In this role, you will work closely with data scientists, engineers, and business stakeholders, transforming advanced models into real‑world, high‑impact applications.
About the Role This is an opportunity to work on end‑to‑end ML systems—from research and experimentation to deployment, monitoring, and continuous improvement.
Responsibilities
Design and implement advanced machine learning and deep learning models, including Transformers, CNNs, and RNNs, aligned to business use cases.
Translate research concepts and prototypes into robust, scalable production solutions.
Build and maintain scalable ML pipelines and REST APIs to serve real‑time and batch predictions.
Partner with engineering teams to integrate models into enterprise applications.
Develop and optimize data pipelines across large and complex datasets.
Perform advanced feature engineering, data validation, and quality checks.
Implement CI/CD pipelines for ML, model versioning, and automated retraining workflows.
Monitor deployed models for performance degradation and model drift, ensuring long‑term reliability.
Generative AI & LLM Integration
Develop and fine‑tune Generative AI solutions, including prompt engineering, RAG (Retrieval‑Augmented Generation), and AI agent workflows.
Experiment with and operationalize LLM‑based architectures for business applications.
Qualifications
Education : Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related STEM field (PhD preferred for research‑oriented roles).
Required Skills
Programming : Expert proficiency in Python (C++ is a plus).
ML Frameworks : Hands‑on experience with PyTorch or TensorFlow, and scikit‑learn.
Data & Analytics : Strong skills in SQL, Pandas, NumPy, and exposure to Apache Spark or similar big‑data tools.
Cloud & MLOps : Experience with at least one major cloud platform such as AWS (SageMaker), Google Vertex AI, or Azure Machine Learning.
Mathematics : Solid foundation in linear algebra, probability, statistics, and calculus.
Preferred Skills
Experience : 3–5+ years of hands‑on experience in machine learning engineering, AI‑focused software development, or applied data science.
Specialization : Experience in one or more areas such as NLP, Computer Vision, large language models (LLMs), or Agentic AI.
Communication : Strong ability to explain complex technical concepts to non‑technical stakeholders and business teams.
Pay range and compensation package Competitive compensation and long‑term career growth in AI & ML.
Equal Opportunity Statement We are committed to diversity and inclusivity.
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