Machine Learning Engineer Lead Level 3 at Kforce Inc in Cincinnati, Ohio

Job Description:

RESPONSIBILITIES:

Kforce has a client in Cincinnati, OH that is seeking a Level 3 Machine Learning Engineer Lead to join their team on a 6-month contract to hire basis.

Responsibilities:

• Machine Learning Engineer will ensure adherence to architecture standards and roadmaps


• Implement overall infrastructure/middleware components per project with infrastructure teams, ensuring that overall solution is designed to meet SLA (performance and up-time), DR, and scalability needs required by the solution


• Design and successfully implement overall infrastructure/middleware components per project with infrastructure teams, ensuring that overall solution is designed to meet SLA (performance and up-time), DR, and scalability needs required by the solution


• Ensure that post-production operational processes/deliverables are well designed and implemented prior to the project moving into the solution support phase


• As a Machine Learning Engineer, you will define and create operational procedures, processes, and scripts


• Follow appropriate change/release management practices


• Support and maintain infrastructure solutions utilizing required tools and technologies


• Provide off-hours support (24 x 7) as required

REQUIREMENTS:

• Strong understanding of machine learning algorithms and principles, especially those relevant to anomaly detection, such as supervised and unsupervised learning, clustering, and neural networks


• Data Handling: Expertise in managing, processing, and analyzing large datasets; Familiarity with data cleaning, data transformation, and feature engineering is crucial


• Programming Skills: Proficiency in programming languages commonly used in machine learning such as Python


• Model Development and Evaluation: Ability to develop robust ML models and evaluate their performance through metrics specific to anomaly detection


• System Integration: Skills to integrate ML models into existing systems for seamless data flow and model deployment including Azure big data and analytics experience


• Analytical Thinking: Ability to analyze complex data and identify patterns or inconsistencies that may indicate problems


• Creative Problem Solving: Capacity to devise innovative solutions that improve detection and prediction of anomalies


• Attention to Detail: Precision in model tuning and the interpretation of data to ensure high accuracy and reliability of outputs


• Clear Communication: Ability to explain complex ML concepts and findings to non-technical stakeholders


• Collaborative Spirit: Willingness to work closely with IT teams, data scientists, and other departments to ensure models align with broader business objectives

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.

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