Artificial Intelligence Machine Learning Engineer Lead
Job Description
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Department: Data Technology
Job Status: Full Time
FLSA: Exempt
Reports to: Data Architecture Manager
Work Location: Hybrid/The Woodlands, TX
Travel Required: 5 - 10%
Work Schedule: Monday - Friday; 8 a.m. - 5 p.m.
Position Supervised: None
AIP: Level 6
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Position Summary:The Artificial Intelligence Machine Learning Engineer Lead will design, develop, and deploy advanced Generative AI and machine learning solutions across the BEUSA family of companies. This role is responsible for building and optimizing Generative AI and traditional ML products, collaborating with cross-functional teams to deliver impactful solutions that drive innovation and efficiency. The Artificial Intelligence Machine Learning Engineer Lead will serve as a technical expert, providing hands-on development and informal mentorship to junior data scientists, and will play a key role in ensuring the successful integration of AI/ML technologies into business processes.
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The ideal candidate is a highly skilled engineer with deep technical expertise in AI/ML, a passion for Generative AI, and a collaborative mindset. This role requires strong problem-solving skills, the ability to work independently, and a desire to stay at the forefront of AI/ML advancements.
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Essential Functions:(The following duties and responsibilities are essential, as defined by the ADA, except those starting with the word "may.")
•AI/ML Solution Development: Design, build, and deploy scalable AI and machine learning models, with a focus on Generative AI applications. Develop robust data pipelines and model training workflows using Python and standard ML libraries.
•Generative AI Innovation: Lead the exploration and implementation of Generative AI models, staying current with emerging trends and evaluating new tools and frameworks for adoption.
•Technical Leadership: Serve as a subject matter expert in AI/ML, providing technical guidance and informal mentorship to junior data scientists. Promote best practices in model development, code quality, and LLMOps/MLOps.
•Scalable AI Solutions: Lead efforts to build scalable and ethical Generative AI solutions that integrate seamlessly within business processes and IT infrastructure. Prioritize efforts in areas such as Generative AI and Machine Learning that have both horizontal and vertical impact.
•Stakeholder Collaboration: Partner with executives, functional teams, and individual stakeholders to understand needs, help set priorities, and ensure AI initiatives are aligned with the overall business strategy and functional group goals.
•AI Ethics & Best Practices: Collaborate with leadership to establish ethical guidelines for AI usage, ensuring transparency, fairness, and accountability in AI-driven solutions.
•Change Advocacy: Promote understanding and adoption of AI across all levels of the organization, training stakeholders on AI’s benefits, risks, and ethical implications.
•Infrastructure & Systems Integration: Partner with IT and data architecture teams to ensure robust data pipelines and infrastructure, enabling the successful deployment and scaling of AI solutions.
•KPI Development & Monitoring: Develop and monitor KPIs to track the success of AI initiatives, providing insights on performance, ROI, and opportunities for improvement.
•Continuous Learning: Stay up to date on emerging trends in Generative AI and traditional data science to ensure the company adopts cutting-edge methods and tools.
•Performs other related duties as assigned to assist with successful operations and business continuity.
POSITION REQUIREMENTS:
•Successfully pass a background check.
•Possess a valid U.S. Driver's License.
•Daily in-person, predictable attendance.
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EDUCATION AND EXPERIENCE
•Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Mathematics, or a related field.
•1+ year of professional experience developing and deploying Generative AI models in production environments.
•5+ years of professional experience developing and deploying machine learning models in production environments.
•Experience with Generative AI models and techniques.
•Experience with Databricks or similar data engineering platforms.
•Oil & Gas industry experience a plus.
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.QUALIFICATIONS, SKILLS, COMPETENCIES, AND ABILITIES:
•Advanced proficiency in Python and standard ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
•Hands-on experience with Generative AI models (e.g., LLMs, prompt engineering, diffusion models).
•Strong understanding of MLOps best practices, including model versioning, monitoring, and CI/CD for ML.
•Experience with cloud environments (e.g., AWS, Azure, GCP) for AI/ML workloads.
•Ability to design and optimize scalable data pipelines and model deployment workflows.
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Business & Communication Skills:
•Excellent verbal and written communication skills, with the ability to present technical topics to both technical and non-technical audiences.
•Proven ability to work independently, manage multiple priorities, and deliver results in a fast-paced environment.
•Experience collaborating with cross-functional teams to deliver business-driven AI/ML solutions.
•Demonstrated ability to mentor and provide technical guidance to junior team members.
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Curiosity & Growth Mindset:
•A high degree of curiosity, with the ability and desire to learn new skills both on-the-fly and in formal learning environments.
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PHYSICAL REQUIREMENTS/WORK ENVIRONMENT
The physical demands and work environment 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.
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Frequently required to walk, sit, climb, bend, reach, and squat/kneel. The Artificial Intelligence Machine Learning Engineer Lead works primarily indoors and will be sitting for prolonged periods at a desk and working on a computer. Must be able to access and navigate each department at the organization’s facilities. The Artificial Intelligence Machine Learning Engineer Lead may be required to lift heavy objects; therefore, the Artificial Intelligence Machine Learning Engineer Lead must be able to lift 25lbs.
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Work hours may include early morning, late afternoon/evening hours, and weekends in combination, depending on job demands.
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AAP /EEO STATEMENT:
The Company is committed to the cause of equal employment opportunity for all employees and applicants, thus abiding by all applicable state and federal laws. Our practices regarding employment, job promotion, compensation, training, and termination do not discriminate on the basis of race, color, religious creed, age, sex, national origin, veteran's status, disability, pregnancy, genetic information, or any other legally protected status. It is expected that all employees, both management and staff, will fully support these nondiscriminatory policies.
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The company has reviewed this job description to ensure essential functions and duties have been included. It is not intended to be an exhaustive list of all functions, responsibilities, skills, and abilities.
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Last Reviewed: 07/2025
full timeThe Woodlands, TX3 days ago
$180,000-$215,000Austin, TX13 days ago
