ML Engineer Jobs at Deloitte with Visa Sponsorship
Deloitte hires ML Engineers across its analytics, AI, and government consulting practices, working on everything from predictive modeling to large-scale AI deployments for enterprise clients. The firm has a consistent track record of sponsoring work visas for technical roles and supports multiple visa pathways for qualified candidates.
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Get Access To All JobsINTRODUCTION
Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey—before, during, and after any major transformational projects or transactions. Are you passionate about leading the charge in emerging technologies? Do you want to join an award-winning team offering diverse opportunities, from account executives and data scientists to AI strategists, machine learning experts, and data engineers? If so, the AI Engineering Manager at SFL Scientific might be the perfect fit. SFL Scientific, a Deloitte Business, is part of our broader Strategy Offering within the Strategy & Transactions practice. Our specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Join us to expand your technical career through leadership, consulting, and becoming an industry leader in the AI engineering community. Recruiting for this role ends on 2/28/2026.
ROLE AND RESPONSIBILITIES
As an AI Engineering Manager/Solutions Architect you will support the design, development, and deployment of novel AI applications across healthcare, life sciences, manufacturing, consumer, energy, and other sectors. You will lead client engagements and design and deliver architecture for complex AI and R&D type problems. AI Engineering Manager are responsible for developing design patterns, infrastructure, and engineering resources by understanding business and use case priorities, defining the data strategy, and leading application deployment to solve our clients' use cases. They work cross-functionally with data scientists, DevOps and data engineers, project managers, and industry experts to develop robust AI platforms and cloud solutions. In our consultative approach, we are platform agnostic and committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, LLM/MLOps, data engineering while streamlining IT and infrastructure. Key responsibilities include but are not limited to:
- Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
- Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
- Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
- Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
- Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
- Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
- Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
- Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
- Mentor, motivate, and coach junior members on technical best practices and inspire professional development
THE TEAM
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation. Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
BASIC QUALIFICATIONS
Required:
- Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
- 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
- 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
- 6+ years of programming experience with Linux Shell/CLI, Python, SQL, Powershell, etc.
- 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
- 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
- 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
- 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
- Live within commuting distance to one of Deloitte's consulting offices
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
PREFERRED QUALIFICATIONS
- Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
- AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
- 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack
COMPENSATION
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $130,800 to $241,000. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
MonitorDeloitte #DeloitteJobs #StrategyConsulting #DeloitteStrategy #Strategy26 #SFL26
INTRODUCTION
Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey—before, during, and after any major transformational projects or transactions. Are you passionate about leading the charge in emerging technologies? Do you want to join an award-winning team offering diverse opportunities, from account executives and data scientists to AI strategists, machine learning experts, and data engineers? If so, the AI Engineering Manager at SFL Scientific might be the perfect fit. SFL Scientific, a Deloitte Business, is part of our broader Strategy Offering within the Strategy & Transactions practice. Our specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Join us to expand your technical career through leadership, consulting, and becoming an industry leader in the AI engineering community. Recruiting for this role ends on 2/28/2026.
ROLE AND RESPONSIBILITIES
As an AI Engineering Manager/Solutions Architect you will support the design, development, and deployment of novel AI applications across healthcare, life sciences, manufacturing, consumer, energy, and other sectors. You will lead client engagements and design and deliver architecture for complex AI and R&D type problems. AI Engineering Manager are responsible for developing design patterns, infrastructure, and engineering resources by understanding business and use case priorities, defining the data strategy, and leading application deployment to solve our clients' use cases. They work cross-functionally with data scientists, DevOps and data engineers, project managers, and industry experts to develop robust AI platforms and cloud solutions. In our consultative approach, we are platform agnostic and committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, LLM/MLOps, data engineering while streamlining IT and infrastructure. Key responsibilities include but are not limited to:
- Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
- Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
- Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
- Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
- Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
- Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
- Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
- Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
- Mentor, motivate, and coach junior members on technical best practices and inspire professional development
THE TEAM
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation. Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
BASIC QUALIFICATIONS
Required:
- Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
- 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
- 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
- 6+ years of programming experience with Linux Shell/CLI, Python, SQL, Powershell, etc.
- 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
- 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
- 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
- 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
- Live within commuting distance to one of Deloitte's consulting offices
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
PREFERRED QUALIFICATIONS
- Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
- AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
- 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack
COMPENSATION
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $130,800 to $241,000. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
MonitorDeloitte #DeloitteJobs #StrategyConsulting #DeloitteStrategy #Strategy26 #SFL26
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Get Access To All JobsTips for Finding ML Engineer Jobs at Deloitte Jobs
Align your portfolio to client delivery
Deloitte's ML Engineer roles sit inside client-facing delivery teams, not pure R&D labs. Tailor your resume and portfolio to show end-to-end model deployment, not just experimentation, since consulting sponsors value production-ready ML work over academic benchmarks.
Target practice areas that file most
Deloitte's Government and Public Services and its AI and Data practice file heavily for technical roles. Applying specifically to openings under these practice areas improves your odds of landing a team with an established sponsorship workflow already in place.
Clarify sponsorship scope before the offer stage
Ask your recruiter whether the role covers H-1B transfer, new cap-subject filing, or both. Some Deloitte business units handle sponsorship centrally through their immigration team; others route it through the engagement partner, which affects how quickly paperwork can move.
Prepare your degree equivalency documentation early
Deloitte frequently submits specialty occupation evidence that leans on degree field alignment. If your ML engineering background comes from a non-U.S. institution or a cross-disciplinary program, get a credential evaluation completed before your offer letter arrives to avoid delays with USCIS.
Use Migrate Mate to filter verified ML Engineer openings
Filtering for Deloitte ML Engineer roles that explicitly flag visa sponsorship saves time during the application phase. Use Migrate Mate to surface and track these openings, so you focus your efforts on positions where sponsorship is already confirmed rather than guessing from the job description.
Understand timing if you need a cap-subject H-1B
If you need a new cap-subject H-1B, registration opens in March for an October 1 start date. Build your Deloitte interview timeline backward from that window so an offer is in hand before the USCIS registration period opens.
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Find ML Engineer at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for ML Engineers?
Yes, Deloitte sponsors H-1B visas for ML Engineers and has done so consistently across its technology and consulting practices. The firm supports both cap-subject petitions for new applicants and H-1B transfers for candidates already holding the status. Sponsorship is typically handled through Deloitte's centralized immigration function, which works with outside counsel to manage filings.
Which visa types does Deloitte commonly sponsor for ML Engineer roles?
Deloitte sponsors H-1B, H-1B1 (for Chilean and Singaporean nationals), and E-3 (for Australian citizens) visas for ML Engineer positions. For candidates pursuing permanent residence, Deloitte also supports EB-2 and EB-3 Green Card sponsorship. The pathway offered depends on your nationality, current status, and the specific practice area you're joining.
What qualifications does Deloitte expect for ML Engineer roles?
Deloitte's ML Engineer roles typically require a bachelor's or master's degree in computer science, statistics, or a closely related quantitative field. Hands-on experience with production ML pipelines, cloud platforms such as AWS or Azure, and frameworks like TensorFlow or PyTorch is expected. Roles in the Government and Public Services practice may also require the ability to obtain a U.S. security clearance.
How do I apply for ML Engineer jobs at Deloitte?
You can apply directly through Deloitte's careers site, filtering by role type and practice area. To find openings that explicitly offer visa sponsorship, browse ML Engineer positions at Deloitte on Migrate Mate, where listings are filtered for confirmed sponsorship. Having your resume tailored to client delivery and production ML work will strengthen your application before you submit.
How do I plan my timeline if I need Deloitte to file an H-1B for me?
If you need a cap-subject H-1B, USCIS opens registration each March for an October 1 fiscal year start. You'll need a signed offer from Deloitte before the registration window to allow their immigration team to register you in the lottery. If you're selected, Deloitte files the full petition between April and June, and your employment can begin on October 1.
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