AI / ML Engineer

Required Skills and Qualifications

• Communication:

  Excellent verbal and written communication, with the ability to explain complex concepts simply and influence decisions.

• AI/ML expertise:

  Strong grounding in machine learning, deep learning, and (ideally) GenAI/LLMs, including RAG and fine-tuning.

• MLOps:

  Hands-on experience with tools such as MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, Azure ML, or Databricks.

• Engineering:

  Strong programming skills (Python required), plus experience with Docker, Kubernetes, and microservices/API design.

• Cloud and data:

  Experience with AWS, Azure, or GCP, and with big data technologies (Spark, Kafka, data lakes/warehouses).

• Stakeholder management:

  A track record of working with senior stakeholders, managing expectations, and delivering across teams.