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Advanced Data Engineer
2 weeks ago
About the Role
We are seeking an experienced Senior MLOps Engineer to join our team at GlobalLogic, a trusted digital engineering partner to the world's largest and most forward-thinking companies. This role will be involved in designing, implementing, and maintaining robust and scalable machine learning pipelines.
This person will possess a strong background in DevOps practices, machine learning principles, and cloud computing platforms. You will work closely with data scientists and software engineers to streamline the deployment and monitoring of machine learning models, ensuring efficiency and reliability in ML operations.
Key Responsibilities
- Designing, implementing, and maintaining robust and scalable machine learning pipelines
- Collaborating with data scientists and software engineers to streamline the deployment and monitoring of machine learning models
- Ensuring efficiency and reliability in ML operations
Requirements
We are looking for someone with:
- Proficiency in programming languages used in ML, such as Python/Java
- Knowledge of software development best practices and methodologies
- Experience with version control systems (e.g., Git)
- Familiarity with CI/CD tools and practices
- Strong problem-solving and analytical skills
- Understanding of data structures and algorithms
- Ability to design and develop scalable, efficient, and maintainable software systems
- Experience with microservice architecture, API development
Machine Learning Skills
- Deep understanding of machine learning principles, algorithms, and techniques
- Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark
- Proficiency in data preprocessing, feature engineering, and model evaluation
- Knowledge of ML model deployment and serving strategies, including containerization and microservices
- Familiarity with ML lifecycle management, including versioning, tracking, and model monitoring
- Ability to optimize and fine-tune ML models for performance and accuracy
- Understanding of statistical analysis and experimental design
- Proficiency in data visualization and interpretation of ML results
Technical Requirements
- Skills with MLOps concepts and principles
- Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes)
- Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI)
What We Offer
- A culture of caring where integrity is key
- Opportunities for continuous learning and development
- Interesting and meaningful work on cutting-edge projects
- A high-trust organization with a commitment to ethics and integrity