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Senior Machine Learning Engineer
Senior Machine Learning EngineerPaycom Payroll Llc • Grapevine, TX, US
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Senior Machine Learning Engineer

Senior Machine Learning Engineer

Paycom Payroll Llc • Grapevine, TX, US
[job_card.30_days_ago]
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  • [job_card.full_time]
[job_card.job_description]

Job Description

Paycom is seeking a motivated AI Engineer with a passion for building practical, innovative solutions. In this role, you will work closely with software engineers to design and implement AI features that enhance our products and improve client experience. You will contribute to the development of AI applications, collaborate with a team of skilled technologists, and gain hands-on experience in applying AI strategies to real-world challenges.

RESPONSIBILITIES

  • Develop, maintain, and improve AI/ML codebases, services and APIs with a focus on reliability and scalability.
  • Collaborate with cross-functional teams including engineers, data scientists, and domain experts to deliver impactful AI solutions.
  • Implement and support AI/ML pipelines for deployment, monitoring and lifecycle management.
  • Automate batch inference workflows and integrate AI features into both internal tools and customer-facing products.
  • Collaborate with engineers, data scientists, and domain experts to deliver impactful AI solutions.
  • Write, clean, testable, and well-documented code to help the team build AI-integrated solutions with confidence.
  • Define architectural changes that can be implemented incrementally, while minimizing risk.
  • Define and evolve model governance, monitoring, drift detection and re-training workflows.
  • Advocate for security and ethical AI practices in compliance with OWASP ML Top 10 and relevant standards.
  • Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or related field

Experience:

  • Hands-on software engineering experience working with AI/ML systems or data-driven applications.
  • Experience developing software utilizing various languages, including Python, SQL and/or the ability to pick up new languages quickly.
  • Strong knowledge and experience using data platforms, machine learning frameworks and generative AI tooling.
  • Experience designing and deploying ML models to production and optimizing MLOps practices
  • Experience with the full lifecycle of software and AI/ML development, including version control, build management, unit testing, CI/CD, API paradigms and model versioning.
  • Experience in deploying and scaling containerized, distributed software and AI systems using tools such as Kubernetes.
  • Depth in using LLMs, including training, fine-tuning, and evaluation. Historical background in “traditional” NLP tools
  • Experience in SOA, Modular Monolith Architecture, and distributed systems for AI training and inference
  • Familiarity with static analysis, code scanning, and ML-specific monitoring tools
  • Knowledgeable in responsible AI and security best practices, including OWASP Top 10 and OWASP ML Top 10
  • Strong collaboration, communication, and problem-solving skills in cross-functional environments.

PREFERRED QUALIFICATIONS

Education/Certification:

  • Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or related field

PHYSICAL DEMANDS

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the employee is regularly required to stand; walk; sit; use hands and fingers to handle, type, or feel; reach with hands and arms; and talk or hear. The employee may occasionally lift and/or move up to 25 pounds. Specific vision abilities required by this job include close vision and ability to adjust focus.

WORK ENVIRONMENT AND ENVIRONMENTAL CONDITIONS

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.

No hazardous or significantly unpleasant conditions. (Such as in a typical office). The noise level in the work environment is usually moderate.

Paycom is an equal opportunity employer and prohibits discrimination and harassment of any kind. Paycom makes employment decisions on the basis of business needs, job requirements, individual qualifications and merit. Paycom wants to have the best available people in every job. Therefore, Paycom does not permit its employees to harass, discriminate or retaliate against other employees or applicants because of race, color, religion, sex, sexual orientation, gender identity, pregnancy, national origin, military and veteran status, age, physical or mental disability, genetic characteristic, reproductive health decisions, family or parental status or any other consideration made unlawful by applicable laws. Equal employment opportunity will be extended to all persons in all aspects of the employer-employee relationship. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, training, promotion, discipline, compensation benefits, and separation of employment. The Human Resources Department has overall responsibility for this policy and maintains reporting and monitoring procedures. Any questions or concerns should be referred to the Human Resources Department. ****To learn more about Paycom's affirmative action policy, equal employment opportunity, or to request an accommodation - Click on the link to find more information: paycom.com/careers/eeoc

BENEFITS: QUALIFICATIONS: Bachelor's Degree, Senior, Full Time
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Senior Machine Learning Engineer • Grapevine, TX, US

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