Senior Level AI ML Engineer Jobs
Senior level ai ml engineer jobs put experienced practitioners in charge of technical direction, model architecture decisions, and the cross-functional projects that bring production systems to life. Roles cover 46% remote and hybrid settings across Technology & Software, Insurance, and Electronics & Hardware, with employers like GEICO, Apple, and General Motors hiring at this level now.
Find JobsOverview
Showing 5 of 25+ Senior Level AI ML Engineer jobs











Role description
AI ML Engineer
ML Engineer I
Who We Are:
Born digital, UST transforms lives through the power of technology. We walk alongside our clients and partners, embedding innovation and agility into everything they do. We help them create transformative experiences and human-centered solutions for a better world.
UST is a mission-driven group of 29,000+ practical problem solvers and creative thinkers in more than 30 countries. Our entrepreneurial teams are empowered to innovate, act nimbly, and create a lasting and sustainable impact for our clients, their customers, and the communities in which we live.
With us, you’ll create a boundless impact that transforms your career—and the lives of people across the world.
Visit us at UST.com.
You Are:
We are seeking a highly skilled AI ML Engineer, with strong Technical Development and data science background to lead the design, development, and deployment of cutting-edge AI-driven product solutions. This role involves collaborating closely with product development, architecture, and management teams to propel the advancement of AI technologies working with business teams and end customers.
The opportunity:
- Build and integrate AI/ML and LLM-driven solutions, including model inference services, data pipelines, and API exposure.
- Develop and maintain modern UI applications using Angular, React ensuring seamless integration with Python backends.
- Deploy, manage, and optimize containerized workloads on Kubernetes on Bare Metal (KOB) platforms.
- Implement end-to-end DevOps practices including CI/CD, infrastructure automation, monitoring, and observability.
- Apply security-by-design principles across application, API, container, and infrastructure layers.
- Collaborate cross-functionally with product, architecture, QA, platform, and security teams to deliver high-quality solutions.
- Ensure code quality through unit testing, integration testing, code reviews, and documentation.
- Drive performance optimization, reliability, and scalability across the full technology stack.
This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.
What you need:
- Python Full stack Development Strong hands-on experience with Python (3.x) for enterprise application development.
- Expertise with FastAPI, Flask, or Django frameworks.
- Proficiency in building RESTful and event-driven APIs. Strong understanding of asynchronous programming, threading, and performance optimization.
- Experience with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis).
- Experience developing and integrating AI/ML solutions into production systems.
- Hands-on exposure to machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Experience with LLMs, prompt engineering, and AI service orchestration is a strong plus.
- Understanding of model lifecycle management, monitoring, and inference performance tuning.
- Data Science tools and visualization tools.
- Strong experience developing applications with Angular Proficiency in TypeScript, RxJS, component-based architecture, and state management.
- Ability to integrate UI with secure backend APIs.
- Familiarity with responsive UI design, accessibility standards, and performance optimization.
- Hands-on experience with Docker and containerization best practices.
- Strong expertise in Kubernetes on Bare Metal (KOB), including: Cluster setup, upgrades, and troubleshooting Networking (CNI), storage (CSI), and ingress configurations High availability and fault tolerance.
- Experience with CI/CD pipelines (Azure DevOps, GitHub Actions, GitLab CI, Jenkins). Infrastructure automation using Terraform, Helm, or similar tools.
- Strong understanding of application and infrastructure security.
- Experience implementing API security (OAuth2, OIDC, JWT, RBAC).
- Familiarity with container and Kubernetes security best practices.
- Knowledge of OWASP Top 10, vulnerability scanning, and secure coding standards.
- Ability to collaborate with security teams on compliance and risk mitigation.
- Strong problem-solving skills and attention to detail.
- Excellent communication and collaboration skills in a global delivery environment.
- Customer-centric mindset with ownership and accountability.
- Demonstrated alignment with positive values, culture, and ethical standards.
- Willingness to mentor junior engineers and contribute to continuous improvement.
- Experience working in large-scale enterprise or regulated environments.
- Exposure to cloud platforms (Azure, AWS, or GCP) alongside on-prem/bare-metal deployments. Knowledge of service mesh, API gateways, or zero-trust architecture.
- Experience with SRE practices, SLAs/SLOs, and reliability engineering.
- Proficiency in project management tools like JIRA, Service Now.
- Ability to manage, motivate, and direct cross-functional teams effectively.
- Excellent written and oral communication, presentation, and stakeholder management skills.
- Flexibility to adapt to challenges and work in periods of ambiguity, converting them into structured direction.
- Typically requires 10+ years of related experience in a professional role with a Master's degree or PhD in computer science or Data Science or AI related fields.
Role Location: Texas
Compensation Range: $72,000-$108,000
Benefits
Full-time, regular employees accrue a minimum of 10 days of paid vacation per year, receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year), 10 paid holidays, and are eligible for paid bereavement leave and jury duty. They are eligible to participate in the Company’s 401(k) Retirement Plan with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance, as well as the following Company-paid Employee Only benefits: basic life insurance, accidental death and disability insurance, and short- and long-term disability benefits. Regular employees may purchase additional voluntary short-term disability benefits, and participate in a Health Savings Account (HSA) as well as a Flexible Spending Account (FSA) for healthcare, dependent child care, and/or commuting expenses as allowable under IRS guidelines. Benefits offerings vary in Puerto Rico.
Part-time employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company’s 401(k) Retirement Plan with employer matching.
Full-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company’s 401(k) program with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance.
Part-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year).
All US employees who work in a state or locality with more generous paid sick leave benefits than specified here will receive the benefit of those sick leave laws.
What we believe:
We proudly embrace the values that have shaped UST since day one. We build our culture of Humility, Humanity, and Integrity. These values inspire us to nurture a people-first, human centric culture that fosters diversity, prioritizes sustainable solutions, and keeps our people and clients at the forefront of all decisions.
Humility:
We will listen, learn, be empathetic and help selflessly in our interactions with everyone.
Humanity:
Through business, we will better the lives of those less fortunate than ourselves.
Integrity:
We honor our commitments and act with responsibility in all our relationships.
Equal Employment Opportunity Statement
UST is an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other applicable characteristics protected by law. We will consider qualified applicants with arrest or conviction records in accordance with state and local laws and “fair chance” ordinances.
UST reserves the right to periodically redefine your roles and responsibilities based on the requirements of the organization and/or your performance.
UST
CB
LI-PK2
Skills
Machine Learning, Data Engineering, Python, Data Science, Generative AI, LLMs, Prompt Engineering, Microservices, Application Security, Kubernetes
Benefits
Compensation range: $72,000.00 to $108,000.00 per year
About UST
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world’s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients’ organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact—touching billions of lives in the process.
See All 25 Senior Level AI ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsSenior Level AI ML Engineer Job Market
Who's Hiring



Top Industries Hiring
- Technology & Software10
- Insurance5
- Electronics & Hardware5
- Banking & Financial Services5
- Investment & Asset Management3
Senior Level AI ML Engineer Jobs: Frequently Asked Questions
How do I get a senior level ai ml engineer job?
Employers hiring at this level look for engineers who have owned the full machine learning lifecycle, from problem framing through deployment and monitoring, not just modeling. Demonstrating that you have driven measurable business impact, mentored junior engineers, and made architecture calls that held up in production gives you a clear edge over candidates who have strong technical skills but limited ownership history.
Which companies hire senior level ai ml engineers?
Companies hiring senior level ai ml engineers right now include GEICO, Apple, and General Motors, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes from a mix of large technology firms building proprietary AI platforms, growth-stage companies scaling ML infrastructure, and enterprises embedding AI into core products across healthcare, finance, and logistics.
Are there remote senior level ai ml engineer jobs?
Yes, remote and hybrid flexibility is common at this level. About 46% of senior level ai ml engineer openings are remote or hybrid as of September 2026, reflecting how many organizations treat senior technical contributors as distributed-team leads. On-site roles do exist, particularly at companies whose work involves sensitive data environments or close collaboration with hardware teams.
What makes an ai ml engineer role senior level?
A senior level role is defined by scope and ownership rather than task execution. Senior engineers set the technical direction for ML systems, evaluate and select frameworks and infrastructure, and are accountable for production reliability at scale. They mentor mid-level engineers, contribute to hiring decisions, and are expected to influence product strategy, not just implement it.
Which industries hire the most senior level ai ml engineers?
Senior level ai ml engineer roles concentrate in Technology & Software, Insurance, and Electronics & Hardware, based on current listings on Migrate Mate as of September 2026. These sectors drive hiring at this level because they have mature data infrastructure, regulatory pressure to automate responsibly, and strategic investments in AI that require engineers who can lead long-horizon technical programs, not just ship models.