What are the responsibilities and job description for the Machine Learning Operations Engineer position at Abacus Service Corporation?
Description :
Note to Suppliers : Each supplier may submit up to candidate. Please ensure you present only your TOP candidates— DO NOT submit just to meet the quota.
Fieldglass Comments Section : Provide a snapshot of key information. (Do not include this on the resume.)
- Candidate's Location : Specify the city.
- Skillset Alignment : Highlight how the candidate's skills align with the role's requirements.
- Requested Time Off : Mention any requested time off, such as vacation.
- Work Authorization Status : Indicate the candidate's work authorization status.
- Is the candidate comfortable with working Pacific Time Zone hours, regardless of physical location?
- Location : Must be able to work Pacific Time Zone hours, regardless of physical location.
- Work location : N. Soto St Los Angeles, CA
- Campus or Medical Enterprise : Medical Enterprise
- Working Job Title : Machine Learning Engineer
- Number of needs :
- Duration of Assignment : This contract is for a duration of months, with a possibility of extension. However, no guarantees are provided regarding the extension
- Work hours : -
- steps Video / Teams interview process
- Dress code : Business Casual
Must-Haves for the Role :
Must be able to work Pacific Time Zone hours, regardless of physical location.
Education :
Bachelor's degree in computer science, artificial intelligence, informatics, or a closely related field.
Master's degree is a plus.
Experience :
At least years of relevant experience as a Machine Learning Engineer.
Proven experience in deploying and maintaining production-grade machine learning models, ensuring real-time inference, scalability, and reliability.
Technical Expertise :
Proficiency in developing end-to-end scalable ML infrastructures using on-premise or cloud platforms such as AWS, GCP, or Azure.
Strong skills in creating and optimizing CI / CD pipelines for machine learning models, including automating testing and deployment processes.
Experience in developing AI pipelines for data ingestion, preprocessing, search, and retrieval.
Competence in setting up monitoring and logging solutions for tracking model performance, system health, and anomalies.
Familiarity with version control systems for tracking changes in ML models and associated code.
Understanding of security and compliance standards related to machine learning systems, including data protection and privacy regulations.
Leadership and Collaboration :
Ability to lead engineering efforts in ML / GenAI model development, LLM advancements, and optimizing deployment frameworks aligned with business strategies.
Demonstrated ability to collaborate with cross-functional teams, including data scientists, data engineers, analytics teams, and DevOps teams.
Documentation and Process Management :
Skilled in maintaining clear and comprehensive documentation of ML Ops processes, workflows, and configurations.
Preferred Qualifications :
Proficiency in containerization technologies such as Docker and Kubernetes.
Knowledge of healthcare standards, regulations, and systems, including integrating ML models with Electronic Health Records (EHR) systems.
Certifications in machine learning or related fields.
Medical Enterprise - Non-Clinical Onboarding - Must complete all onboarding requirements prior to the start date, with no exceptions.
Medical Enterprise - Non-Clinical Onboarding Requirements :
Background, Education, and Employment
Background Check :
Education :
Employment :
Other Requirements :
Medical Requirements :
Immunizations :
TB Test :
Drug Screen :
o Amphetamines
o Barbiturates
o Benzodiazepines
o Cocaine metabolite
o Opiates (Codeine, Morphine)
o Hydrocodone
o Hydromorphone
o Oxycodone
o Phencyclidine
o Methadone
o Propoxyphene
Influenza Vaccination :
COVID Vaccinations :
Note : All items are billable except for the drug screen.
Qualified Applicants with arrest or Conviction records will be considered for Employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act
Working Job Title Machine Learning Operations Engineer Markup Category Information Technology Shift Details / Expected Working Days and Hours SEE JD Dress Code / Special Attire Business Casual Does this position require driving? No Will resource have direct patient contact? No HIPAA training required? Yes Nearest Parking Location SEE JD Will job responsibilities include working directly with minors? No Does the position allow for the worker to be virtual / remote? Yes Shore Options Available for this Position Onshore Only Hours per Day Hours per Week Total Hours ,
