Machine Learning Specialist

Key Responsibilities:

• Lead the architecture, design, and implementation of complex AI/ML models and systems.
• Collaborate with data scientists, ML engineers, and product teams to build scalable and production-ready solutions.
• Develop, test, and maintain high-performance Python applications and machine learning pipelines.
• Research and evaluate new tools, frameworks, and technologies in AI/ML to drive innovation.
• Design and oversee model training, validation, deployment, and monitoring strategies.
• Ensure best practices in code quality, model performance, reproducibility, and system scalability.
• Mentor junior engineers and contribute to technical leadership across the team.
• Manage project timelines, risks, and delivery in a fast-paced Agile environment.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• 7+ years of experience in software engineering, with at least 3+ years in AI/ML model development and deployment.
• Strong proficiency in Python and relevant libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.
• Solid experience with machine learning algorithms, deep learning, NLP, computer vision, or recommendation systems.
• Experience deploying models to production (e.g., using Docker, REST APIs, Flask/FastAPI, or MLflow).
• Familiarity with MLOps, CI/CD pipelines, and cloud platforms (AWS, GCP, or Azure).
• Strong knowledge of software engineering principles, data structures, and system design.

Nice to Have:

• Experience with big data frameworks like Spark, Kafka, or Hadoop.
• Exposure to Kubernetes or container orchestration.
• Contributions to open-source projects or published research.
• Understanding of ethical AI practices, model fairness, and explainability.