Key skills
AWSAzureCloudDjangoDockerFlaskGoogle Cloud PlatformGrafanaJenkinsKerasKubernetesNumpyPandasPrometheusPythonPyTorchTensorflowTerraformAIMLOpenAIAnthropicTensorFlowNumPyFastAPIGCPGoogle CloudGitHub ActionsGitLab CICloudFormationGitHubGitLabAgileCI/CDCommunication
About this role
Role Overview
- Designing, building, and automating ML pipelines.
- Deploying and scaling models in production.
- Monitoring, maintaining, and improving model performance.
- Collaborating with Data Engineers and client stakeholders.
- Establishing governance, documentation, and best practices.
Requirements
- Strong expertise in Python and AI frameworks such as PyTorch, Keras, SciPy, or Tensorflow.
- Experience with Python-based Web frameworks like FastAPI, Flask, or Django.
- Knowledge of PEP 8 coding standards for Python.
- Extensive experience in solving AI/ML challenges and working with LLMs.
- Familiarity with OpenAI, Embeddings, Completion, and Semantic Search.
- Solid experience with API integrations and working with external APIs like OpenAI, Anthropic, or similar AI service providers.
- Hands-on experience with containerization and orchestration tools – especially Docker for packaging ML models, and Kubernetes (or similar) for deploying and scaling them in distributed environments.
- Proficiency in DevOps and automation practices: designing CI/CD pipelines (using tools like Jenkins, GitLab CI/CD, or GitHub Actions) to automate model testing and deployment, and using Infrastructure-as-Code (CloudFormation, Terraform) to manage cloud resources.
- Working knowledge of cloud computing services (AWS, Azure, GCP) for ML workloads.
- Familiarity with databases and experience using SQLAlchemy, Alembic, and database management for AI models.
- Strong skills in managing datasets using tools like Pandas, SciPy, and Numpy for data pre/post-processing.
- Experience with monitoring and logging frameworks; Prometheus/Grafana or cloud monitoring services.
- Strong analytical and problem-solving skills to diagnose issues from logs/metrics and tune system performance.
- Excellent communication skills and a collaborative mindset;
- Ability to work in an agile environment, manage priorities, and coordinate with remote or cross-functional team members is important.
Tech Stack
- AWS
- Azure
- Cloud
- Django
- Docker
- Flask
- Google Cloud Platform
- Grafana
- Jenkins
- Keras
- Kubernetes
- Numpy
- Pandas
- Prometheus
- Python
- PyTorch
- Tensorflow
- Terraform
Benefits
- Flexible work arrangements
- Professional development