Machine Learning Engineer

Responsibilities

Kforce has a client that is seeking a Machine Learning Engineer in Durham, NC. Responsibilities:

• Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models
• Machine Learning Engineer will partner with Data Scientists and to help use the foundational platform upon which models can be built and trained
• Operationalize ML Models at scale (e.g., Serve predictions on tens of millions of customers)
• Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics
• As a Machine Learning Engineer, you will explore new technology trends and leveraging them to simplify our data and ML ecosystem
• Driving Innovation and implementing solutions with future thinking
• Guiding teams to improve development agility and productivity
• Resolving technical roadblocks and mitigating potential risks
• Delivering system automation by setting up continuous integration/continuous delivery pipelines

Requirements

• Bachelor's or Master's degree in a technology related field (e.g. Engineering, Computer Science, etc.)
• 5+ years of proven experience in implementing big data solutions in data analytics space
• 1+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS SageMaker
• Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required
• Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python's ML ecosystem (NumPy, pandas, sklearn, TensorFlow, etc.)
• Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks
• Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent)
• Solid experience in Agile methodologies (Kanban and Scrum)
• Strong knowledge of developing highly scalable distributed systems using Open-source technologies
• Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

Salary: $83 - $90 per hour