Machine Learning Specialist

We are looking for a Machine Learning Specialist to design, develop, deploy, and optimize AI and machine learning solutions from research through production. You will work with cross-functional teams to build scalable ML applications, improve model performance, and implement MLOps best practices that deliver business value.

Key Responsibilities:

• Research and evaluate state-of-the-art machine learning and generative AI techniques.
• Design, develop, fine-tune, and optimize machine learning models for business use cases such as fraud detection, credit scoring, and personalization.
• Build and maintain data pipelines, feature engineering processes, and training datasets.
• Deploy and manage ML models using Docker, Kubernetes, CI/CD, and MLOps practices.
• Develop APIs and integrate AI solutions into enterprise applications.
• Monitor model performance, implement version control, drift detection, and model governance.
• Collaborate with Data Engineers, Software Engineers, and Product Owners in an Agile environment.
• Produce technical documentation, conduct code reviews, and share best practices with the team.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Statistics, Mathematics, Physics, or a related quantitative field.
• 3+ years of experience in Machine Learning Engineering, Data Science, or AI Research.
• Strong programming skills in Python and SQL.
• Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience building, training, and deploying ML models in production environments.
• Experience with Git, Docker, Kubernetes, CI/CD, and MLOps practices.
• Strong understanding of model evaluation, optimization, explainability, and AI security.
• Excellent analytical, problem-solving, and communication skills.

Nice to Have

• Experience with Generative AI, LLMs, NLP, recommender systems, or graph-based machine learning.
• Experience with PEFT, LoRA, QLoRA, or other LLM fine-tuning techniques.
• Knowledge of AWS, Azure, or Google Cloud AI services.
• Master's degree or PhD in a related field.
• Published AI/ML research or open-source contributions.