Machine Learning Manager Jobs at Deloitte with Visa Sponsorship
Machine Learning Manager roles at Deloitte sit at the intersection of advanced AI development and client-facing consulting, leading teams that build and deploy models across industries like financial services, healthcare, and government. Deloitte has a strong track record of sponsoring international talent across multiple visa categories for this function.
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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 Machine Learning Manager Jobs at Deloitte Jobs
Align your credentials to consulting project demands
Deloitte's ML Manager roles require demonstrating client delivery experience, not just model-building. Frame your resume around business outcomes from ML deployments rather than research output. Hiring managers evaluate whether you can lead client-facing engagements.
Target Deloitte's federal and commercial AI practices
Deloitte staffs ML Managers across distinct practice areas. Federal contracts often have security clearance implications that affect sponsorship eligibility. Focus your applications on commercial sector AI or analytics practices to avoid clearance-related restrictions on visa-sponsored candidates.
Use Migrate Mate to filter verified sponsorship openings
Deloitte posts ML Manager roles across multiple platforms, but not all listings indicate sponsorship availability. Use Migrate Mate to surface roles where Deloitte has confirmed sponsorship history for this specific function and visa type.
Clarify your visa category before the offer stage
Deloitte sponsors H-1B, H-1B1, E-3, and employment-based Green Cards. If you're an Australian citizen, ask your recruiter explicitly about the E-3 pathway early. It processes faster than H-1B and skips the lottery, which matters if your OPT or current status has a hard deadline.
Prepare for specialty occupation documentation specific to ML
USCIS scrutinizes Machine Learning roles to confirm they meet specialty occupation standards. Gather job description language, your degree transcripts, and any published work or patents before your offer stage so Deloitte's immigration counsel can build a strong I-129 petition quickly.
Account for PERM timing if a Green Card is your goal
If Deloitte offers EB-2 or EB-3 sponsorship, PERM labor certification through DOL adds significant time before an I-140 can be filed. For nationals from high-backlog countries, understand your priority date implications before accepting an offer that hinges on permanent residency.
Machine Learning Manager at Deloitte jobs are hiring across the US. Find yours.
Find Machine Learning Manager at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for Machine Learning Managers?
Yes, Deloitte sponsors H-1B visas for Machine Learning Manager roles. Because H-1B is subject to the annual cap and lottery, timing matters. If you're already on an H-1B with another employer, Deloitte can file a transfer petition outside the cap. New applicants without existing H-1B status must go through the lottery, typically registering in March for an October 1 start date.
How do I apply for Machine Learning Manager jobs at Deloitte?
Apply directly through Deloitte's careers portal, where ML Manager roles are listed by practice area and location. Tailor your application to highlight client delivery experience alongside technical depth. You can also use Migrate Mate to browse Deloitte's verified sponsorship-friendly ML Manager openings and filter by visa type before applying, which helps you target roles where sponsorship has been confirmed.
Which visa types does Deloitte commonly sponsor for Machine Learning Manager roles?
Deloitte sponsors H-1B, H-1B1, and E-3 visas for nonimmigrant work authorization, as well as EB-2 and EB-3 immigrant visa categories for employees pursuing a Green Card. Australian citizens are often well-positioned for the E-3 pathway, which has no lottery and allows biennial renewals. H-1B1 applies to Chilean and Singaporean nationals under specific free trade agreements.
What qualifications does Deloitte expect for a Machine Learning Manager?
Deloitte typically expects a graduate degree in computer science, statistics, or a related quantitative field, combined with several years of experience leading ML projects in a professional services or enterprise environment. Demonstrated ability to manage cross-functional teams, translate business problems into model requirements, and present results to senior stakeholders carries as much weight as technical proficiency in the evaluation process.
How long does the sponsorship and onboarding process take at Deloitte?
Timeline depends on your visa category. E-3 and H-1B transfers can move in four to eight weeks with USCIS premium processing. New H-1B cap-subject petitions require the October 1 start date, meaning offers made after April may involve a months-long wait. PERM-based Green Card sponsorship adds a year or more before the I-140 stage, so confirming Deloitte's sponsorship scope during negotiation is important.
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