Senior AI/ML Engineer

Key Responsibilities

Design and implement advanced machine learning, deep learning, and AI models across domains such as NLP, computer vision, recommendation systems, and generative AI.

Oversee data strategy, including preprocessing, feature engineering, and large-scale data pipelines.

Drive adoption of MLOps best practices for model development, deployment, and monitoring.

Lead and mentor a team of data scientists, ML engineers, and analysts.

Collaborate with stakeholders to understand business problems and define data-driven solutions.

Stay up to date with the latest advancements in AI/ML and evaluate their potential application.

Ensure models are explainable, ethical, and aligned with regulatory/compliance requirements.

Primary (Must-Have) Skills

Strong foundation in Mathematics, Statistics, and Machine Learning theory.

Proficiency in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch, Hugging Face).

Proven expertise in NLP, Computer Vision, or Generative AI (Transformers, RAG, LLMs, CNNs, Vision Transformers).

Hands-on experience with Big Data technologies (Spark, Hadoop, Kafka, Hive).

Strong knowledge of SQL and data pipelines.

Experience with cloud platforms (Azure ML, AWS SageMaker, or GCP AI Platform).

Understanding of MLOps (CI/CD, Docker, Kubernetes, model monitoring).

Secondary (Good-to-Have) Skills

Programming experience in Java/Scala/R.

Familiarity with web/backend integration (REST APIs, Django, FastAPI, Spring Boot).

Knowledge of data governance, ethics, and compliance in AI.

Strong business acumen and ability to translate insights into strategies.

Excellent communication, leadership, and stakeholder management skills.