Sr Developer

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What We'll Bring:

What You'll Bring:

Job Summary:

We are seeking a highly experienced and innovative AI/ML Engineer to lead the design, development, and deployment of scalable machine learning solutions. The ideal candidate will have deep expertise in Python, Apache Spark, MLOps, and cloud platforms (GCP and AWS), along with experience in distributed query engines like Trino. You will play a key role in building intelligent systems that drive business value through data science and machine learning.

Key Responsibilities:

• Design and implement scalable ML pipelines using Spark, Python, and MLOps best practices.
• Develop, train, and deploy machine learning models in production environments.
• Collaborate with data scientists, data engineers, and product teams to translate business problems into ML solutions.
• Optimize model performance and ensure reproducibility, versioning, and monitoring using MLOps tools and frameworks.
• Work with Trino and other distributed query engines for efficient data access and feature engineering.
• Deploy and manage ML workloads on GCP and AWS, leveraging services like SageMaker, Vertex AI, BigQuery, and EMR.
• Implement CI/CD pipelines for ML workflows and ensure compliance with data governance and security standards.
• Mentor junior engineers and contribute to the development of best practices and technical standards.

Required Skills:

• Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Expertise in Apache Spark for large-scale data processing.
• Solid understanding of MLOps practices including model versioning, monitoring, and deployment.
• Experience with Trino or similar distributed SQL engines (e.g., Presto, Hive).
• Hands-on experience with GCP (e.g., Vertex AI, BigQuery) and AWS (e.g., SageMaker, S3, Lambda).
• Familiarity with containerization (Docker) and orchestration (Kubernetes).
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.

Preferred Qualifications:

• Master’s or PhD in Computer Science, Data Science, or a related field.
• Experience with feature stores, model registries, and ML observability tools.
• Knowledge of data privacy, security, and compliance in ML systems.
• Contributions to open-source ML or data engineering projects.

Impact You'll Make:

NA

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