Machine Learning Engineer
As a Senior Machine Learning Engineer, you will lead the development and implementation of sophisticated data engineering solutions to support the deployment and optimization of AI models. Your role will involve demonstrating extensive experience in designing robust, scalable, and innovative data architectures that align with the unique requirements of Artificial Intelligence applications.
Job Location: Hybrid (preferred base cities - Atlanta, NYC, Dallas, Houston, Chicago, San Fran, and Seattle)
Key Responsibilities:
- The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance, research, and innovation supporting production AI systems.
- Build and maintain data engineering solutions on cloud platforms using hyperscaler services (GPC, AWS, Azure).
- Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, and data lakes).
- Develop and maintain data models and schema designs to support efficient data storage and retrieval.
- Use hyperscaler technologies to support data needs for the expansion of Machine Learning/Data Science capabilities including generative AI.
- Implement data validation and data cleansing processes to ensure data quality and consistency.
- Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark, and API integrations.
- Monitor ETL jobs, troubleshoot issues, and ensure data processing efficiency.
- Administer and optimize databases, ensuring performance, scalability, and data security.
- Collaborate with multi-functional teams to understand data requirements and integrate data into various applications and analytics platforms.
- Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high-performing data pipeline solutions.
- Ensure compliance with data privacy and security regulations.
- Optimize data systems for scalability and performance, anticipating and addressing potential bottlenecks.
- Document changes, versioning, and standard processes
- Strong communication skills and the ability to work effectively in a collaborative environment.
- Excellent problem-solving and troubleshooting abilities, along with a strong analytical mentality and persistence in resolving problems.
- Stay updated on emerging data engineering technologies and best practices.
Required Skills:
- Bachelor's degree in computer science, data engineering, or a related field with 5+ years experience (Master's preferred).
- Proven experience in data engineering, ETL, and database management.
- Proficiency in SQL and data manipulation languages.
- Proven experience deploying solutions in Azure
- Strong programming skills, with knowledge of languages like Python, Java, or Scala.
- Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models.
- Experience with data warehousing platforms (e.g., Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
- Experience with database technologies for structured and unstructured data both for storage and optimal retrieval
- Experience with highly scalable Data stores, Data Lakes, Data Warehouses, Lakehouse, and unstructured datasets
- Familiarity with data modeling and schema design.
- Knowledge of data integration tools and data orchestration.
- Excellent problem-solving and troubleshooting skills.
- Strong communication and collaboration abilities.
Life at Capgemini:
When you join our data and AI community, you become part of a proud global collective of expert enthusiasts and lifetime learners, who use the transformative power of data and AI to drive a positive impact for our clients, people, society, and our planet. Explore the community - https://www.capgemini.com/careers/career-paths/professions/data-and-ai/
Capgemini supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer:
- Flexible work
- Healthcare including dental, vision, mental health, and well-being programs
- Financial well-being programs such as 401(k) and Employee Share Ownership Plan
- Paid time off and paid holidays
- Paid parental leave
- Family-building benefits like adoption assistance, surrogacy, and cryopreservation
- Social well-being benefits like subsidized backup child/elder care and tutoring
- Mentoring, coaching and learning programs
- Employee Resource Groups
- Disaster Relief