Machine Learning Consultant Jobs
Machine Learning Consultant jobs are open across technology, finance, healthcare, and professional services, from junior consultant to principal and staff levels, with specializations in NLP, computer vision, and MLOps. Find a role that fits below and apply directly.
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At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.
Job Description
Team and overall scope:
- The Allstate's Data & Analytics Technology organization is seeking a Machine Learning Platform Lead to architect, build, and scale the core platforms that power enterprise-wide machine learning solutions.
- In this role, you will provide deep technical leadership across ML infrastructure, MLOps automation, model deployment systems, and cloud-native engineering. You will influence platform strategy, guide architectural decisions, and collaborate closely with data science, engineering, security, and product teams to enable reliable, scalable, and responsible ML adoption across the enterprise.
This role is ideal for a senior technologist who thrives in hands-on engineering, technical leadership, and building high-impact ML platform capabilities.
Key Responsibilities
- Serve as the technical lead for ML platform architecture, guiding system design, scalability, performance, and reliability across platform components.
- Architect and build core ML platform services, including training and compute infrastructure, feature stores, model registries, inference runtimes, and data pipelines.
- Drive architectural decisions for distributed systems, cloud‑native frameworks, and automated MLOps workflows that support enterprise-scale machine learning.
- Evaluate and integrate emerging ML platform technologies, tools, and best practices to continuously strengthen platform capabilities.
- Design and implement robust MLOps pipelines for experiment tracking, data and model versioning, CI/CD for ML, automated retraining, and model governance.
- Develop automated workflows that ensure reproducible model training, validation, deployment, and lifecycle management across multiple environments.
- Implement monitoring and observability systems for model performance, data quality, drift detection, and inference reliability.
- Build and optimize cloud-based ML infrastructure on Azure, AWS, or GCP using Kubernetes, containerization, and infrastructure‑as‑code.
- Develop scalable batch and streaming data pipelines using modern data engineering tools and frameworks.
- Embed security, compliance, responsible AI principles, and cost optimization best practices within ML platform architecture and operations.
- Collaborate with data scientists to translate modeling needs into scalable, reusable, and self-service platform capabilities.
- Work closely with security, compliance, and governance teams to ensure safe and compliant deployment of AI/ML solutions.
- Partner with application engineering teams to accelerate adoption of ML services and enable consistent, high-quality production deployments.
- Provide technical mentorship, set engineering standards, and contribute to documentation, best practices, and ongoing platform improvements.
Required Qualifications
- Extensive experience in ML engineering, platform engineering, or large-scale distributed systems.
- Deep hands-on expertise with MLOps tools, ML frameworks, model deployment techniques, and ML lifecycle automation.
- Strong proficiency in Python and backend development for machine learning systems.
- Experience with cloud platforms and ML services, including Azure ML Studio, AWS SageMaker, and/or Google Vertex AI.
- Exposure to cloud storage/data such as Azure Fabric/OneLake, AWS S3, and Google Cloud Storage (GCS).
- Experience with cloud-native scanning and security tools such as Azure Defender, Microsoft Purview, AWS Security Hub, Amazon Inspector, GCP Security Command Center, or equivalent services.
- Strong understanding of technologies such as Kubernetes, Docker, CI/CD, Terraform/Infrastructure-as-Code, etc.
- Solid knowledge of system design, APIs, data pipelines, and scalable ML infrastructure patterns.
- Proven ability to lead technical initiatives and influence cross‑team engineering decisions. 6+ years of progressive related experience
Skills
CI/CD, Machine Learning (ML), Machine Learning Model Development, Machine Learning Operations, Microsoft Azure, Python Automation, Python FrameworksCompensation
Compensation offered for this role is 110,000.00 - 181,025.00 annually and is based on experience and qualifications.The candidate(s) offered this position will be required to submit to a background investigation.
Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.
Allstate generally does not sponsor individuals for employment-based visas for this position.
Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.
For jobs in San Francisco, please click “here” for information regarding the San Francisco Fair Chance Ordinance.
For jobs in Los Angeles, please click “here” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance.
To view the “EEO Know Your Rights” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs.
To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint.
It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.
Allstate provides a comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse. Employees eligible to work from home also receive a monthly connectivity reimbursement to help offset internet costs.
When working from home, you must have a dedicated, private workspace free from distractions, along with appropriate desk and seating. Reliable internet is required, with minimum speeds of 50 MB download and 5 MB upload.
To help create a more personal and engaging experience, we ask that you join with your camera on if your interview is virtual. Please also have a Valid Photo Identification available at the start of your interview. If you require any accommodations or have questions ahead of your interview please reach out to your recruiter.
Note: Internal candidates are only asked to join on video; a Valid Photo Identification is not needed for the interview.
At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.
Job Description
Team and overall scope:
- The Allstate's Data & Analytics Technology organization is seeking a Machine Learning Platform Lead to architect, build, and scale the core platforms that power enterprise-wide machine learning solutions.
- In this role, you will provide deep technical leadership across ML infrastructure, MLOps automation, model deployment systems, and cloud-native engineering. You will influence platform strategy, guide architectural decisions, and collaborate closely with data science, engineering, security, and product teams to enable reliable, scalable, and responsible ML adoption across the enterprise.
This role is ideal for a senior technologist who thrives in hands-on engineering, technical leadership, and building high-impact ML platform capabilities.
Key Responsibilities
- Serve as the technical lead for ML platform architecture, guiding system design, scalability, performance, and reliability across platform components.
- Architect and build core ML platform services, including training and compute infrastructure, feature stores, model registries, inference runtimes, and data pipelines.
- Drive architectural decisions for distributed systems, cloud‑native frameworks, and automated MLOps workflows that support enterprise-scale machine learning.
- Evaluate and integrate emerging ML platform technologies, tools, and best practices to continuously strengthen platform capabilities.
- Design and implement robust MLOps pipelines for experiment tracking, data and model versioning, CI/CD for ML, automated retraining, and model governance.
- Develop automated workflows that ensure reproducible model training, validation, deployment, and lifecycle management across multiple environments.
- Implement monitoring and observability systems for model performance, data quality, drift detection, and inference reliability.
- Build and optimize cloud-based ML infrastructure on Azure, AWS, or GCP using Kubernetes, containerization, and infrastructure‑as‑code.
- Develop scalable batch and streaming data pipelines using modern data engineering tools and frameworks.
- Embed security, compliance, responsible AI principles, and cost optimization best practices within ML platform architecture and operations.
- Collaborate with data scientists to translate modeling needs into scalable, reusable, and self-service platform capabilities.
- Work closely with security, compliance, and governance teams to ensure safe and compliant deployment of AI/ML solutions.
- Partner with application engineering teams to accelerate adoption of ML services and enable consistent, high-quality production deployments.
- Provide technical mentorship, set engineering standards, and contribute to documentation, best practices, and ongoing platform improvements.
Required Qualifications
- Extensive experience in ML engineering, platform engineering, or large-scale distributed systems.
- Deep hands-on expertise with MLOps tools, ML frameworks, model deployment techniques, and ML lifecycle automation.
- Strong proficiency in Python and backend development for machine learning systems.
- Experience with cloud platforms and ML services, including Azure ML Studio, AWS SageMaker, and/or Google Vertex AI.
- Exposure to cloud storage/data such as Azure Fabric/OneLake, AWS S3, and Google Cloud Storage (GCS).
- Experience with cloud-native scanning and security tools such as Azure Defender, Microsoft Purview, AWS Security Hub, Amazon Inspector, GCP Security Command Center, or equivalent services.
- Strong understanding of technologies such as Kubernetes, Docker, CI/CD, Terraform/Infrastructure-as-Code, etc.
- Solid knowledge of system design, APIs, data pipelines, and scalable ML infrastructure patterns.
- Proven ability to lead technical initiatives and influence cross‑team engineering decisions. 6+ years of progressive related experience
Skills
CI/CD, Machine Learning (ML), Machine Learning Model Development, Machine Learning Operations, Microsoft Azure, Python Automation, Python FrameworksCompensation
Compensation offered for this role is 110,000.00 - 181,025.00 annually and is based on experience and qualifications.The candidate(s) offered this position will be required to submit to a background investigation.
Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.
Allstate generally does not sponsor individuals for employment-based visas for this position.
Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.
For jobs in San Francisco, please click “here” for information regarding the San Francisco Fair Chance Ordinance.
For jobs in Los Angeles, please click “here” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance.
To view the “EEO Know Your Rights” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs.
To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint.
It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.
Allstate provides a comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse. Employees eligible to work from home also receive a monthly connectivity reimbursement to help offset internet costs.
When working from home, you must have a dedicated, private workspace free from distractions, along with appropriate desk and seating. Reliable internet is required, with minimum speeds of 50 MB download and 5 MB upload.
To help create a more personal and engaging experience, we ask that you join with your camera on if your interview is virtual. Please also have a Valid Photo Identification available at the start of your interview. If you require any accommodations or have questions ahead of your interview please reach out to your recruiter.
Note: Internal candidates are only asked to join on video; a Valid Photo Identification is not needed for the interview.
Machine Learning Consultant Jobs by Experience Level
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Find JobsMachine Learning Consultant Job Market
Who's Hiring
Top Industries Hiring
- Accounting & Auditing
What Employers Look For
The qualifications that appear most often in machine learning consultant jobs.
- Proficiency in Python and core ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience designing and deploying models in cloud environments such as AWS, Azure, or GCP
- Strong understanding of MLOps practices including CI/CD pipelines, model monitoring, and versioning
- Ability to communicate technical findings and recommendations clearly to non-technical stakeholders
- Experience with data engineering fundamentals including SQL, ETL pipelines, and feature stores
- Bachelor's or master's degree in computer science, statistics, mathematics, or a related quantitative field
Tips for Your Machine Learning Consultant Job Search
Tailor your resume to deployment depth
Hiring managers for machine learning consultant roles want to see models you shipped, not just built. For each project, name the framework, the data scale, and the production outcome. Notebooks and research prototypes that never deployed carry far less weight.
Show client-facing work in your portfolio
Consulting roles weigh communication as heavily as technical skill. Include a case study or write-up where you translated a machine learning solution into a business recommendation. Code alone does not demonstrate the consulting half of this job title.
Apply early to roles that fit
Migrate Mate lists machine learning consultant openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter by the engagement model
Machine learning consultant postings split between staff-augmentation contracts, project-based engagements, and full-time embedded roles. Each has a different interview process and day-to-day scope. Reading the engagement type before applying saves you from preparing for the wrong kind of conversation.
Prepare a whiteboard scoping exercise
Many interviews for this role include a live problem-framing exercise where you define success metrics, data requirements, and a rollout plan before writing any code. Practice narrating your thought process out loud, not just arriving at a solution, because interviewers are evaluating how you would lead a client through ambiguity.
Negotiate scope before negotiating compensation
In consulting roles, the deliverables and engagement length often matter as much as the base rate. Before discussing compensation, clarify what a successful engagement looks like, what tools and data access you get, and whether the role includes a path to extension or conversion.
Machine Learning Consultant Jobs: Frequently Asked Questions
Which companies are hiring the most machine learning consultants?
Amazon Web Services, EY, and Inspire11 are hiring the most machine learning consultants right now, with openings concentrated in Virginia, New York, and Illinois, based on current listings on Migrate Mate as of November 2026. Demand is especially high at consulting firms with dedicated AI and data practices as well as large technology companies scaling internal ML platforms.
How many machine learning consultant jobs are remote?
About 100% of machine learning consultant openings are fully remote or hybrid as of November 2026, reflecting the project-based and deliverable-driven nature of consulting work. Sub-areas like NLP engineering, model evaluation, and responsible AI auditing tend to have the highest share of fully remote roles, while engagements that require on-site client workshops or data-room access are more likely to be hybrid or on-site.
How do you become a machine learning consultant?
Start by building a foundation in applied machine learning through industry projects, open-source contributions, or graduate coursework, then develop client-facing skills through internal advisory roles, freelance engagements, or teaching. Earning a cloud certification from a major provider strengthens your profile. Most consultants enter from a data science, ML engineering, or software engineering background before moving into an advisory capacity.
Can you get a machine learning consultant job without prior consulting experience?
Yes, you can break into machine learning consulting without a formal consulting background if your technical portfolio demonstrates end-to-end delivery and you can articulate your work in business terms. Many hiring managers value depth in a specific domain, such as healthcare or fintech, over prior consulting titles. Freelance or contract projects that involved client communication are particularly useful as proxies for consulting experience.
What does the machine learning consultant interview process look like?
The process typically moves through a recruiter screen, a technical assessment covering coding and ML fundamentals, and a case or system-design interview where you scope a solution to a realistic business problem. Final rounds often include a presentation to stakeholders or a panel with both technical and business leads. Some firms add a written case study submitted before the final interview.
Where can I find and apply to machine learning consultant jobs?
You can find and apply to machine learning consultant jobs on Migrate Mate, which lists current openings from across the United States in one place. Find roles that match your background and apply directly to each listing without being redirected to multiple external sites.
See All 16 Machine Learning Consultant Jobs
Find roles that match your experience and apply in just a few clicks.
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