Machine Learning Engineer Jobs at Deloitte with Visa Sponsorship
Deloitte hires Machine Learning Engineers across its AI and analytics practices, working on client-facing data solutions in consulting, federal, and industry verticals. The company has a consistent track record of sponsoring work visas for this function, supporting candidates from the offer stage through to long-term status.
See All Machine Learning Engineer at Deloitte JobsOverview
Showing 5 of 151+ Machine Learning Engineer Jobs at Deloitte jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 151+ Machine Learning Engineer Jobs at Deloitte
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer Jobs at Deloitte.
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
See all 151+ Machine Learning Engineer at Deloitte jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer at Deloitte roles.
Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Deloitte Jobs
Frame your ML portfolio around client deliverables
Deloitte's ML roles are delivery-focused, not pure research. Structure your portfolio around production models, client-facing tools, or measurable business outcomes rather than academic benchmarks or notebook experiments.
Target Deloitte's AI and Analytics practice directly
Deloitte hires ML Engineers across multiple practices, but AI and Analytics has the highest concentration of these roles. Filter your applications to that practice area to avoid being screened against unrelated consulting tracks.
Prepare your specialty occupation documentation now
For H-1B petitions, USCIS requires evidence that the role qualifies as a specialty occupation. Gather your degree transcripts, any credential evaluations, and role-specific job description documentation before your employer's immigration counsel requests them.
Check current job openings using Migrate Mate
Deloitte posts Machine Learning Engineer roles across multiple portals and practices. Use Migrate Mate to filter active openings specifically flagged for visa sponsorship eligibility, so you're applying to roles where sponsorship is already confirmed.
Align your start date with H-1B cap timelines if applicable
If you need a cap-subject H-1B, USCIS registration opens in March for an October 1 start date. Confirm with Deloitte's recruiting team whether your role qualifies for cap-exempt filing through a client site, which would remove that constraint.
Machine Learning Engineer at Deloitte jobs are hiring across the US. Find yours.
Find Machine Learning Engineer at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for Machine Learning Engineers?
Yes, Deloitte sponsors H-1B visas for Machine Learning Engineers. The company works with immigration counsel to file petitions for qualifying roles across its consulting and technology practices. If your role is delivered at a qualifying institution, it may also be eligible for cap-exempt H-1B filing, which avoids the annual lottery.
How do I apply for Machine Learning Engineer jobs at Deloitte?
Applications go through Deloitte's careers portal, though roles are also aggregated on Migrate Mate where you can filter specifically for positions that include visa sponsorship. Tailor your resume to reflect client-impact language and production ML experience, as Deloitte's screening process emphasizes applied, delivery-oriented skills over research backgrounds.
Which visa types does Deloitte commonly sponsor for Machine Learning Engineers?
Deloitte sponsors H-1B and H-1B1 visas for most international ML hires, along with the E-3 for Australian citizens. For candidates pursuing permanent residence, Deloitte supports EB-2 and EB-3 Green Card sponsorship through the PERM labor certification process. The applicable pathway depends on your nationality, degree, and role classification.
What qualifications does Deloitte expect for Machine Learning Engineer roles?
Most postings require a bachelor's or master's degree in computer science, statistics, or a related quantitative field, along with hands-on experience in Python, model deployment, and cloud platforms like AWS or Azure. For H-1B purposes, the degree must align with the role's specialty occupation classification, so a directly relevant field of study strengthens your petition.
How long does the visa sponsorship process take at Deloitte for this role?
For cap-subject H-1B petitions, plan for registration in March, a lottery result in late March or April, and a petition filing deadline before June 30 for an October 1 start. E-3 processing at a U.S. consulate typically takes two to four weeks after documents are ready. PERM-based Green Card sponsorship runs longer, often 18 to 36 months depending on your priority date and country of birth.
See which Machine Learning Engineer at Deloitte employers are hiring and sponsoring visas right now.
Search Machine Learning Engineer at Deloitte Jobs