Interested in this AI/ML Engineer role at Baker Tilly Canada?
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About This Role
Overview
Baker Tilly is a leading advisory, tax and assurance firm, providing clients with a genuine coast-to-coast and global advantage in major regions of the U.S. and in many of the world’s leading financial centers – New York, London, San Francisco, Los Angeles, Chicago and Boston. Baker Tilly Advisory Group, LP and Baker Tilly US, LLP (Baker Tilly) provide professional services through an alternative practice structure in accordance with the AICPA Code of Professional Conduct and applicable laws, regulations and professional standards. Baker Tilly US, LLP is a licensed independent CPA firm that provides attest services to its clients. Baker Tilly Advisory Group, LP and its subsidiary entities provide tax and business advisory services to their clients. Baker Tilly Advisory Group, LP and its subsidiary entities are not licensed CPA firms.
Baker Tilly Advisory Group, LP and Baker Tilly US, LLP, trading as Baker Tilly, are independent members of Baker Tilly International, a worldwide network of independent accounting and business advisory firms in 141 territories, with 43,000 professionals and a combined worldwide revenue of $5.2 billion. Visit bakertilly.com or join the conversation on LinkedIn, Facebook and Instagram.
Please discuss the work location status with your Baker Tilly talent acquisition professional to understand the requirements for an opportunity you are exploring.
Baker Tilly is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, gender identity, sexual orientation, or any other legally protected basis, in accordance with applicable federal, state or local law.
Any unsolicited resumes submitted through our website or to Baker Tilly Advisory Group, LP, employee e-mail accounts are considered property of Baker Tilly Advisory Group, LP, and are not subject to payment of agency fees. In order to be an authorized recruitment agency ("search firm") for Baker Tilly Advisory Group, LP, there must be a formal written agreement in place and the agency must be invited, by Baker Tilly's Talent Attraction team, to submit candidates for review via our applicant tracking system.
Job Description:
AI Solutions Engineer
Are you passionate about business and technology coming together to deliver the future of finance and accounting services to a variety of clients?
Would you like to work with one of the fastest growing professional services firms in the country who are an industry leader in technology implementations?
If so, consider joining Baker Tilly as an AI Solutions Engineer, where you’ll build intelligent, autonomous agentic solutions that streamline business processes, integrate with enterprise systems, and help shape the future of AI-enabled work at Baker Tilly.
As one of the fastest growing firms in the nation, BT has the ability to offer you upward career trajectory, flexibility in how and where you get your work done and meaningful relationships with clients, teammates and leadership who truly care about you and your development.
Does this describe you?
You want to work for a leading professional services firm whose owners have both their clients’ and employees’ best interests in mind and are transparent in their decisions
You want to grow professionally and develop your client service and technical skills to build a career with endless opportunities now, for tomorrow
What you will do:
- Team with colleagues and clients to provide the following services: + Aid in the scope, design, and build applications and infrastructure-related components for our application hosting solutions. + Develop utilities, tools, data fixes, and Sage Intacct page-level customizations to support internal staff to during the implementation process and to support specialized initiatives for internal projects + Communicate effectively with internal staff, external development vendors, development teams of customers, etc.
- Invest in your professional development individually and through participation in firm wide learning and development programs
- Support the growth and development of team members through the Baker Tilly Care and Teach philosophy, helping associates meet their professional goals
- Enjoy friendships, social activities and team outings that encourage a work-life balance
Successful candidates will have:
- Bachelor's degree or higher in Computer Science, Information Technology or related degree required
- Five (5) plus years of experience developing applications in a cloud-based environment (specifically AWS.
- Significant hands-on experience designing and developing AI/Agent-based solutions including developing agents on MCP servers on Amazon Bedrock Agent Core and integrating with LLM provider APIs.
- Optimizing AI-based solutions for token efficiency and performance.
- Experience integrating data between systems using APIs
- Hands on experience developing solutions using AI development tools such as Cursor, Windsurf, and Claude Code.
- Strong understanding of AWS architecture, services, and features, specifically containers, serverless architecture, security, networking, etc.
- Experience with development languages and frameworks, with emphasis on Python and JavaScript. Additionally, PHP, NodeJS, and React are a bonus.
- Experience with databases (RDBMS, NoSQL, etc.) is desired
- Excellent analytical, technical and problem-solving skills, with strong attention to detail.
- Exceptional verbal and written communication, collaboration, and time management skills.
- Ability to work in the US without sponsorship required.
The pay range for this position is $100,000 to $182,400. This range represents a good-faith and reasonable estimate of the compensation the firm expects to pay for this position at the time of posting. Actual compensation will depend on a variety of relevant factors, including an applicant’s skills, experience, qualifications, professional certifications, work arrangements, geographic location, and other business and organizational needs. It is not typical for an individual to be hired at or near the top of the range, and compensation decisions depend on the facts and circumstances of each case. Baker Tilly offers a compensation and benefits package to eligible employees.
Salary Context
This $100K-$182K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 2239 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Baker Tilly Canada, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,040 based on 13,780 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($141K) sits 33% below the category median. Disclosed range: $100K to $182K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Baker Tilly Canada AI Hiring
Baker Tilly Canada has 5 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Irvine, CA, US, Walnut Creek, CA, US, San Diego, CA, US. Compensation range: $182K - $400K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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