MLOps Engineer

Top Skills' Details 3+ years of experience working on building and deploying data pipelines in AWS- lambda, S3, ECS 1+ year of experience deploying ML and AI models to AWS - creating the DevOps pipelines to deploy Experience developing in Python Description Role Overview We are seeking an experienced MLOps / Data Engineer to work closely with Data Science, Data Engineering, and Cloud teams to design, implement, and operationalize machine learning solutions in AWS. This is a hands-on engineering role focused on taking Data Science workloads from experimentation into reliable, scalable, production-grade ML pipelines and services. The ideal candidate combines strong MLOps engineering, AWS cloud, and Data Engineering experience and has a demonstrated track record of partnering directly with Data Scientists to productionize machine learning models. Core Responsibilities MLOps & ML Productionization • Design, build, and maintain production-grade MLOps pipelines. • Productionize machine learning models developed by Data Science teams. • Implement automated workflows covering: o Data preparation o Feature engineering o Model training o Model validation o Model deployment o Model monitoring o Retraining • Establish and improve CI/CD practices for machine learning workloads. • Implement model versioning, artifact management, experiment tracking, and reproducibility. • Develop monitoring for model performance, data quality, data drift, and operational health. • Troubleshoot production ML pipelines and improve reliability, scalability, and observability. AWS MLOps The candidate must have demonstrated hands-on experience implementing MLOps solutions within AWS. Relevant technologies may include: • Amazon S3 • AWS Lambda • Amazon ECR • Amazon ECS/EKS • AWS Step Functions • Amazon EventBridge • AWS IAM • Amazon CloudWatch • AWS CodePipeline / CodeBuild or equivalent CI/CD tooling • Amazon SageMaker • SageMaker Pipelines • SageMaker Model Registry • AWS Glue The candidate should understand how to design secure and scalable ML architectures using AWS services rather than simply having general AWS exposure. Data Engineering Design and implement reliable data pipelines supporting machine learning and analytical workloads. Responsibilities may include: • Building scalable ETL/ELT pipelines. • Creating curated datasets for Data Science and ML applications. • Implementing data validation and data-quality controls. • Developing reusable data transformation frameworks. • Optimizing pipelines for performance, scalability, and cost. • Integrating structured and unstructured data from multiple sources. • Supporting batch and, where applicable, event-driven or streaming workloads. • Implementing appropriate logging, monitoring, and error handling. Data Science Partnership Work directly with Data Scientists to bridge the gap between experimentation and production. The engineer will be expected to: • Understand Data Science experimentation workflows. • Convert notebooks and prototype code into production-grade solutions. • Help Data Scientists establish reproducible development and deployment processes. • Create reusable frameworks that allow Data Scientists to deploy models more efficiently. • Identify engineering, scalability, security, and operational requirements before models enter production. • Collaborate on feature engineering, model packaging, deployment, monitoring, and retraining strategies. Required Qualifications Candidates should demonstrate: 1. Proven MLOps Experience • Hands-on experience building and operating production ML systems. • Experience deploying ML models into production environments. • Strong understanding of the complete ML lifecycle. • Experience with CI/CD and automation for ML workloads. • Experience with model monitoring, versioning, and reproducibility. 2. Proven AWS MLOps Experience • Demonstrated experience implementing production MLOps solutions on AWS. • Strong practical knowledge of AWS architecture and services used for ML workloads. • Experience with SageMaker and/or comparable AWS-native ML deployment patterns. • Understanding of AWS security, IAM, networking, monitoring, and infrastructure considerations. 3. Proven Data Engineering Experience • Strong Python and SQL skills. • Experience designing and building production ETL/ELT pipelines. • Experience working with large datasets and distributed processing technologies. • Experience implementing data quality, validation, and monitoring. • Strong understanding of data modeling and data pipeline architecture. 4. Experience Working with Data Science Teams • Demonstrated experience partnering directly with Data Scientists. • Experience taking Data Science models from notebooks/prototypes into production. • Ability to translate Data Science requirements into scalable engineering solutions. • Ability to communicate technical tradeoffs to both engineering and Data Science stakeholders. Preferred Technical Skills Strong experience with several of the following: • Python • SQL • AWS • Amazon SageMaker • AWS Glue • Amazon S3 • Lambda • Step Functions • Docker • Kubernetes / EKS • Terraform or AWS CDK • Git • CI/CD • MLflow or equivalent experiment/model management platforms • Airflow or equivalent workflow orchestration platforms • Spark / PySpark • Databricks, where applicable Skills Python, Aws, data engineering, machine learning Top Skills Details Python,Aws,data engineering,machine learning Additional Skills & Qualifications Ideally would like someone in South FL that could come to office 1-2x per month Strong communication and proactive attitude Experience Level Intermediate Level Job Type & Location This is a Contract position based out of Juno Beach, FL. Pay and Benefits The pay range for this position is $45.00 - $60.00/hr. Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors. 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 fully remote position. Application Deadline This position is anticipated to close on Aug 28, 2026. About TEKsystems We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company. The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law. About TEKsystems and TEKsystems Global Services We’re a leading provider of business and technology services. We accelerate business transformation for our customers. Our expertise in strategy, design, execution and operations unlocks business value through a range of solutions. We’re a team of 80,000 strong, working with over 6,000 customers, including 80% of the Fortune 500 across North America, Europe and Asia, who partner with us for our scale, full-stack capabilities and speed. We’re strategic thinkers, hands-on collaborators, helping customers capitalize on change and master the momentum of technology. We’re building tomorrow by delivering business outcomes and making positive impacts in our global communities. TEKsystems and TEKsystems Global Services are Allegis Group companies. Learn more at TEKsystems.com. 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. San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records. Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.