Machine Learning Data Enigneer

Position Overview:

We are seeking an experienced MLOps Engineer to join our team and to help drive the development and deployment of scalable machine learning infrastructure. In this role, you will collaborate closely with a team of data scientists, software engineers, and cloud engineers to design, implement, and manage robust MLOps pipelines and infrastructure in AWS. Expertise in Terraform, Kubernetes, and cloud-native solutions will be critical in provisioning and automating resources to support machine learning workflows. Automating SDLC with GitHub actions, bash and python scripts, and infrastructure as code to meet requirements will also be essential.

Roles/Responsibilities:

• Work closely with data scientists, software engineers, product managers, and stakeholders to understand the requirements, challenges, and opportunities of machine learning projects.
• Design, build, and maintain scalable and reliable data pipelines and platforms that support the development and deployment of machine learning models and applications.
• Apply best practices and tools to ensure the quality, reliability, scalability, and security of machine learning pipelines and systems.
• Optimize the performance, efficiency, and reliability of the data pipelines and platforms.
• Monitor and troubleshoot the data pipelines and platforms and resolve any issues or errors.
• Document and maintain development standards, best practices, and procedures.
• Continuously learn and improve your skills and knowledge in the fast-changing field of machine learning.

• Bachelor's degree in computer science, engineering, mathematics, statistics, or related field.
• At least 6 years of experience in machine learning, data engineering, or software engineering.
• Proficient in Python and one or more of the following frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, etc.
• Familiar with programming languages such as Java, Scala.
• Experience with data processing and storage technologies such as Spark, Hadoop, SQL, NoSQL, etc.
• Experience with cloud computing platforms and services such as AWS, Azure, Google Cloud Platform, etc.
• Experience with AWS SageMaker, AWS Glue, AWS EMR is a plus.
• Experience with machine learning lifecycle management tools such as MLflow, Kubeflow, Airflow, etc.
• Experience with containerization and orchestration technologies such as Docker, Kubernetes, etc.
• Experience with version control, testing, and CI/CD tools such as Git, GitHub, Jenkins, etc.
• Knowledge of machine learning concepts and techniques such as supervised, unsupervised, and reinforcement learning, deep learning, natural language processing, computer vision, etc.
• Ability to communicate effectively and collaborate with cross-functional teams.
• Ability to work independently and creatively, and solve complex problems.
• Passion for learning and innovation.

• Machine Learning
• Data Analysis
• AWS Cloud Formation
• Python
• Java
• Hadoop

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.