Description

Our end client is looking for a ML Ops Automation Engineer to work on the team's data science initiatives. We are seeking a skilled and experienced ML Ops Engineer to join our team. This role will be crucial in bridging the gap between data science and production, ensuring the reliable and scalable deployment of machine learning models. You will be responsible for building and maintaining the infrastructure, automation, and processes that enable our data science teams to deliver high-quality AI/ML solutions. The ideal candidate will possess a strong understanding of AWS, infrastructure as code, CI/CD pipelines, and the operational aspects of running machine learning workloads.

Responsibilities:

•\tDevelop and maintain robust, scalable, and secure infrastructure on AWS to support the entire ML lifecycle, from data ingestion to model deployment and monitoring.

•\tDevelopment experience on AWS using python libraries to provision resource and handle workloads.

•\tAutomate the deployment of machine learning models and associated infrastructure using Infrastructure as Code (IaC) tools like Terraform or CloudFormation.

•\tDesign and implement CI/CD pipelines for machine learning models, enabling continuous integration, testing, and deployment.

•\tBuild and operate AWS backend applications to support ML model serving, monitoring, and data processing.

•\tImplement monitoring and alerting systems to ensure the health and performance of ML models and infrastructure.

•\tCollaborate with data scientists and engineers to understand their needs and translate them into operational requirements.

•\tProactively identify and resolve infrastructure bottlenecks and optimize resource utilization.

•\tContribute to the development of best practices for ML Ops within the organization.

•\tSupport the troubleshooting and debugging of issues across the ML pipeline.

•\tPromote knowledge sharing and best practices within the team.

•\tEnsure the security and compliance of the ML infrastructure and data.

•\tPerform Data Engineering tasks as needed to ensure smooth data flow to ML models

Additional Skills & Qualifications

•\tStrong scripting and automation skills using Python (required)

•\tExperience working with AWS services (EC2, S3, ECS/EKS, SageMaker, Lambda, IAM, etc.) (required)

•\tExperience with Infrastructure as Code tools (Terraform, CloudFormation) (required)

•\tStrong knowledge of CI/CD concepts and tools (Git, Jenkins, Gitlab CI, AWS CodePipeline) (required)

•\tExperience deploying and managing ML models in production (required)

•\tExperience working with containerization technologies such as Docker and Kubernetes (good to have)

•\tKnowledge of data science tools, packages and ML models (good to have)

•\tExperience with monitoring and alerting tools (Cloudwatch, Prometheus, Grafana) (good to have)

•\tExperience with security concepts and best practices (good to have)

Job Requirements:

•\tBS/MS in computer science, engineering, or a related field with 4-6 years of relevant experience.

•\tProven experience in designing, building, and operating production-grade ML infrastructure and pipelines.

•\tStrong understanding of cloud computing, especially AWS.

•\tDemonstrated experience with automation, configuration management, and Infrastructure as Code.

•\tStrong knowledge of CI/CD principles and practices.

•\tExperience with deploying and managing containerized applications.

•\tExperience building and deploying AWS backend applications.

•\tStrong problem-solving and troubleshooting skills.

•\tExcellent communication and collaboration skills.

•\tAbility to work independently and in a team environment.

•\tStrong work prioritization, planning, and organizational skills.

•\tStrong documentation skills with attention to detail.

•\tDemonstrated ability to work independently with minimal oversight throughout the entire lifecycle of a project.

•\tAgile mindset.

•\tBroad knowledge and experience in the various domains of information technology.

Additional Qualifications (Good to have):

•\tAWS Certifications (e.g., AWS Certified DevOps Engineer, AWS Certified Solutions Architect)

•\tExperience with data engineering tools and techniques

•\tExperience with security technologies

•\tExperience with various ML Ops tools and platforms

•\tAbility to develop automation scripts using various tools and technologies

Pay and Benefits

The pay range for this position is $60.00 - $63.00

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:

• Medical, dental & vision
• Critical Illness, Accident, and Hospital
• 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
• Life Insurance (Voluntary Life & AD&D for the employee and dependents)
• Short and long-term disability
• Health Spending Account (HSA)
• Transportation benefits
• Employee Assistance Program
• Time Off/Leave (PTO, Vacation or Sick Leave)

Workplace Type

This is a hybrid position in Durham,NC.

Application Deadline

This position will be accepting applications until Jan 24, 2025.

About Actalent

Actalent is a global leader in engineering and sciences services and talent solutions. We help visionary companies advance their engineering and science initiatives through access to specialized experts who drive scale, innovation and speed to market. With a network of almost 30,000 consultants and more than 4,500 clients across the U.S., Canada, Asia and Europe, Actalent serves many of the Fortune 500.

Diversity, Equity & Inclusion

At Actalent, diversity and inclusion are a bridge towards the equity and success of our people. DE&I are embedded into our culture through:

Hiring diverse talent Maintaining an inclusive environment through persistent self-reflection Building a culture of care, engagement, and recognition with clear outcomes Ensuring growth opportunities for our people

The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please email actalentaccommodation@actalentservices.com for other accommodation options.