Posted:
10/4/2024, 9:31:17 AM
Location(s):
Oklahoma, United States ⋅ Tulsa, Oklahoma, United States
Experience Level(s):
Mid Level ⋅ Senior
Field(s):
AI & Machine Learning ⋅ Data & Analytics
Workplace Type:
Hybrid
JOB SUMMARY
We are seeking a skilled MLops Engineer to join our enterprise Advanced Analytics and Data Science team where we are solving challenging and impactful business problems by leveraging AI, ML, and other advanced algorithms. The MLops Engineer role is essential for optimizing our data product lifecycles, from development to deployment and scaling. The ideal candidate will be passionate about AI, well-versed in cloud technologies, and adept at automating and operating ML systems.Job Profile Summary
This role will lead advanced data analytics and machine learning projects to uncover critical insights and drive innovation, ensuring the implementation of best practices. This role acts as a bridge between data science teams and business leadership. The ideal candidate will have extensive experience in data science, exceptional problem-solving skills, and the ability to communicate technical information effectively to stakeholders at all levels.
Essential Functions and Responsibilities
Collaborate with data scientists to develop and integrate ML and AI algorithms into efficient, scalable cloud deployments.
Design and implement robust MLOps pipelines, with IaC, to automate model training, testing, deployment, and monitoring.
Collaborate with Data Engineers to design, develop, and maintain real time, event driven feature pipelines.
Implement a continuous improvement framework to monitor, evaluate, and improve data product pipelines to ensure they meet business requirements.
Manage the infrastructure and data pipelines, including data observability, quality, uptime, and cost optimization.
Education
Bachelor's Degree Quantitative field (Finance, Economics, Math, Engineering, Science), Computer Science, Computer Engineering, Information Technology, Systems Analysis or a related study preferred
Work Experience
Minimum of 3 - 5 years related work experience
Expert proficiency in Python and machine learning frameworks (TensorFlow, PyTorch), with a strong foundation in statistical methods and data analysis techniques.
Experience with data engineering and architecture, including SQL, NoSQL, and Vector databases.
Strong knowledge of DevOps, CI/CD tools (ADO, GitLab), and infrastructure as code (Cloud Formation, Terraform).
Experience with AWS cloud services (SageMaker, Redshift, Glue, Lambda).
Excellent problem-solving skills and the ability to work in a fast-paced environment.
Knowledge, Skills and Abilities
Skills in: Technical Skills: Advanced proficiency in data analysis tools and programming languages (e.g., Python, R, SQL). Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
Skills in: Analytical Skills: Strong analytical and problem-solving abilities with a proven track record of developing complex models and algorithms.
Skills in: Communication Skills: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical audiences.
Skills in: Leadership Skills: Demonstrated ability to lead, mentor, and manage a team of data professionals. Strong project management skills are essential.
Ability to: Strategic Vision: Ability to develop and execute data science strategies that align with business objectives.
Skills in: Collaboration: Strong interpersonal skills and the ability to work effectively with cross-functional teams and senior management.
Skills in: Innovation: A proactive approach to identifying new opportunities and improving existing processes through data science.
Ability to: Adaptability: Flexibility to adapt to changing business needs and evolving technology landscapes.
Licenses and Certifications
None required
Strength Factor Rating - Physical Demands/Requirements
Sedentary Work - Exerting up to 10 pounds of force occasionally (Occasionally: activity or condition exists up to 1/3 of the time) and/or a negligible amount of force frequently (Frequently: activity or condition exists from 1/3 to 2/3 of the time) to lift, carry, push, pull, or otherwise move objects, including the human body. Sedentary work involves sitting most of the time, but may involve walking or standing for brief periods of time. Jobs are sedentary if walking and standing are required only occasionally and all other sedentary criteria are met.
Strength Factor Description - Physical Demands/Requirements
Standing: Remaining on one's feet in an upright position at a work station without moving about (Occasionally)
Walking: Moving about on foot (Frequently)
Sitting: Remaining in a seated position (Constantly)
Lifting: Raising or lowering an object from one level to another (includes upward pulling) (Occasionally)
Carrying: Transporting an object, usually holding it in the hands or arms, or on the shoulder (Occasionally)
Pushing: Exerting force upon an object so that the object moves away from the force (Occasionally)
Pulling: Exerting force upon an object so that the object moves toward the force (includes jerking) (Occasionally)
Climbing: Ladders, Stairs (Occasionally)
Balancing: Maintaining body equilibrium to prevent falling (Occasionally)
Stooping: Bending the body downward and forward by bending the spine at the waist (Occasionally)
Kneeling: Bending the legs at the knees to come to rest on the knee or knees (Occasionally)
Crouching: Bending the body downward and forward by bending the legs and spine (Occasionally)
Crawling: Moving about on the hands and arms in any direction (Occasionally)
Reaching: Extending hands and arms in any direction (Constantly)
Handling: Seizing, holding, grasping, turning or otherwise working with the hand or hands (Manual Dexterity) (Constantly)
Fingering: Picking, pinching or otherwise working with the fingers primarily (Finger Dexterity) (Constantly)
Feeling: Perceiving such attributes of objects/materials as size, shape, temperature, texture, movement or pulsation by receptors in the skin, particularly those of the finger tips (Constantly)
Talking: Expressing or exchanging ideas/information by means of the spoken word (Frequently)
Hearing: Perceiving the nature of sound by the ear (Frequently)
Tasting/Smelling: (Occasionally)
Near Vision: Clarity of vision at 20 inches or less (Constantly)
Far Vision: Clarity of vision at 20 feet for more (Frequently)
Depth Perception: Three-dimensional vision; ability to judge distances and spatial relationships so as to see objects where and as they actually are (Frequently)
Vision: Color - The ability to identify and distinguish colors (Constantly)
Working Conditions/Environment
Employee is subject to inside environmental conditions
Working Conditions
Well lighted, climate controlled areas (Constantly)
Frequent repetitive motion (Constantly)
CRT (Computer Monitor(s)) (Constantly)
Travel
<10%
Driving
Based on assigned tasks, employee may be assigned a company vehicle requiring the applicable driver's license
ONEOK is an equal opportunity employer committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, sex, pregnancy, sexual orientation, age, religion, creed, national origin, gender identity, disability, military/veteran status, genetic information or any other categories protected by applicable law.
The job description is not intended to be a complete list of all responsibilities, duties or skills required for the job and is subject to review and change at any time, with or without notice, in accordance with the needs of ONEOK.
ONEOK is committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request an accommodation email [email protected] or call 1-855-663-6547.
#LI-Hybrid
Expected Salary Range
$111,000.00 - $167,000.00Website: https://oneok.com/
Headquarter Location: Tulsa, Oklahoma, United States
Employee Count: 1001-5000
Year Founded: 1906
IPO Status: Public
Last Funding Type: Post-IPO Debt
Industries: Automotive ⋅ Energy ⋅ Logistics ⋅ Oil and Gas ⋅ Transportation