Interested in this AI/ML Engineer role at Circuit Check Inc?
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About This Role
About the job
Who we are:
Circuit Check is the market\-leading provider of automated test systems and test fixtures for complex electronic products for the automotive, military/aerospace, medical, industrial, and computer networking industries. At Circuit Check, we believe that innovation is a must, and that a challenging and robust environment where the work is consistently new and cutting edge is the best way to foster creativity. If you are ready to further your career in a fast\-paced, technology driven organization where our test designs impact products that are used by millions of people around the world every day, then we invite you to join us at Circuit Check.Our design staff includes electrical, software, mechanical engineers, and project managers. Our systems are supported by staff throughout the United States, Canada, Mexico, Europe, Malaysia, and China.
Primary Objective
Lead the strategic development and growth of Circuit Check’s most significant customer relationships in the AI/ML data center infrastructure market. Architect and execute multi\-year account strategies that drive large\-scale program wins, deepen executive\-level partnerships, and position the company as the preferred technology partner for hyperscale and enterprise AI customers. This role does not carry a traditional sales quota; compensation includes bonus objectives tied to winning new large customers, capturing major programs, and expanding strategic account revenue.
Major Areas of Accountability
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Strategic Account Leadership
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- Develop and own multi\-year strategic account plans for the company’s largest AI/ML infrastructure customers, anticipating market shifts and positioning ahead of competitive threats
- Analyze customer technology roadmaps, capital expenditure patterns, and buying dynamics to identify high\-value opportunities across GPU test, thermal management, power delivery, and related segments
- Serve as the primary executive\-level interface with strategic accounts, building trusted advisor relationships with VP and C\-suite decision\-makers at hyperscale cloud providers, AI chipmakers, and data center operators
- Take decisive ownership of high\-stakes negotiations, complex proposals, and multi\-million\-dollar program pursuits, differentiating Circuit Check solutions
Cross\-Functional Program Orchestration
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- Coordinate engineering, product management and operations around customer requirements
- Partner with Product Line Managers to translate customer insights into product roadmap inputs aligned with AI/ML market direction
- Drive program management cadence for strategic accounts: pipeline reviews, executive business reviews, win/loss analysis, and quarterly assessments
Market Intelligence \& Growth Strategy
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- Identify patterns in AI/ML technology adoption, supply chain shifts, and customer investment priorities that create strategic openings for Circuit Check
- Quantify new market opportunities through analysis of TAM, competitive dynamics, segment profitability, and technology adjacencies; present data\-supported recommendations to senior leadership
- Build and maintain industry relationships across the AI/ML ecosystem, including suppliers, contract manufacturers, analysts, and technology partners worldwide
International Business Development
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- Develop and execute customer engagement strategies in key AI/ML hubs, with emphasis on Silicon Valley and Taiwan
- Navigate international business environments including multi\-stakeholder decision processes and cultural dynamics across Asia\-Pacific
- Represent the company at international conferences, trade shows, and executive briefings as an authoritative voice on AI/ML infrastructure
Sales Team Collaboration \& Mentorship
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- Mentor less experienced sales team members on complex deal strategy, multi\-stakeholder navigation, and executive engagement
- Partner with assigned account team members who maintain day\-to\-day relationships, providing strategic direction while developing their capabilities
- Collaborate with Sales Leadership to build playbooks and best practices for pursuing large AI/ML infrastructure programs
Education \& Experience
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- Bachelor’s degree in Engineering (Electrical, Mechanical, or related) required; MBA or advanced technical degree preferred
- 10\+ years of progressive experience in strategic account management, business development, or program leadership in semiconductor, electronic hardware, test \& measurement, data center infrastructure, or related technology sectors
- Track record of winning and managing multi\-million\-dollar programs with complex, multi\-stakeholder customer organizations
- Strongly preferred: executive\-level relationships at hyperscale cloud providers; experience in the AI/ML hardware ecosystem (GPU test/validation, liquid cooling, power distribution, rack\-scale integration, or related infrastructure)
- International business experience preferred, especially in the Taiwan semiconductor ecosystem and/or SE Asian manufacturing
Knowledge, Skills \& Abilities
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Strategic \& Analytical Thinking
- Ability to see patterns across complex data, customer behaviors, and market signals — and translate insights into actionable strategies and business cases
- Rigorous analytical skills: financial models, program economics, pricing structures, and competitive intelligence that inform decision\-making
- Thinks several moves ahead — anticipating customer needs, competitive responses, and market evolution
Organizational \& Execution Leadership
- Natural ability to orchestrate multiple moving parts — people, timelines, resources, priorities — across complex programs and matrixed organizations
- Skilled at configuring cross\-functional teams for maximum effectiveness, with the program management discipline to track interdependencies and keep engagements on schedule and budget
Presence \& Influence
- Commanding executive presence with confidence to lead negotiations, challenge the status quo, and drive decisions in ambiguous situations
- Willingness to take charge, confront difficult issues directly, and provide clear direction when the path forward is uncertain
- Exceptional communication skills — compelling narratives, proposals, and presentations for technical and executive audiences
Industry \& Technical Acumen
- Deep understanding of the AI/ML data center ecosystem: GPU architectures, training/inference infrastructure, thermal management, power delivery, rack integration, and test/validation
- Credible in technical discussions with customer engineering teams while maintaining a business\-outcome focus; proficient with CRM platforms (Salesforce preferred)
Compensation \& Performance Structure
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This role does not carry a traditional sales quota. Compensation includes a competitive base salary plus bonus objectives tied to:
- Winning new strategic AI/ML customers and capturing large new programs with existing accounts
- Growth in strategic account revenue and program pipeline value
- Program execution milestones and customer satisfaction metrics
Location \& Travel Requirements
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- Open to remote candidates in the United States, with a preference for candidates in the San Francisco Bay Area, California
- Travel expected up to 50%, including customer visits throughout the Bay Area, across the US, and periodic international travel to Taiwan and SE Asia
- Must possess a valid passport and ability to obtain required travel visas
Physical Requirements
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*These physical requirements must be performed with or without accommodation:*
- Time split between office/home office, customer sites, and travel
- Ability to sit for extended periods; bend, reach, stoop, and twist as required
- Heavy computer use; occasional exposure to manufacturing or lab environments
- Ability to lift and carry up to 25 lbs
*This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required of the employee. Duties, responsibilities, and activities may change at any time with or without notice.*
Pay and Benefits
*This job description reflects management’s assignment of key responsibilities; it does not prescribe or restrict the tasks that may be assigned.*
Individual base pay is based on various factors, including work location, relevant experience and skills, the responsibility of the role, and job duties/requirements. For this role, our current base pay range is $120,000 \- $200,000\.
Listed range represents the full earning potential in this position. Starting salaries for well\-qualified new hires are typically around the midpoint of the range. This range was determined by a market\-based compensation approach; we used data from trusted third\-party compensation sources to set equitable, consistent, and competitive ranges. We also evaluate compensation annually, identify any changes in the market and make adjustments to our ranges and existing employee compensation as needed.
Base pay is only one element of an employee's total compensation at Circuit Check. Employees (and their dependents in most plans) are covered by medical, dental, vision, basic life, short\- and long\-term disability and accidental death and dismemberment insurance. Employees are able to enroll in Circuit Check’s 401k plan, in which the Company will match 50% of your contributions up to 6% with a maximum contribution. Paid time off includes vacation and sick time along with paid holidays. A summary of benefits can be provided by request via email to [email protected].
Circuit Check, Inc. is proud to be an Equal Opportunity Employer. We do not discriminate based on identity, race, color, religion, national origin or ancestry, sex (including sexual identity), age, physical or mental disability, pregnancy, veteran or military status, genetic information, sexual orientation, marital status, or any other legally recognized protected basis under federal, state, or local law. Because Circuit Check is a federal contractor, we participate in the E\-Verify program in certain locations, as required by law. Applicants must be legally authorized to work in the United States without needing sponsorship for an employment visa (e.g., H1B status).
If you need a reasonable accommodation for any part of the employment process, please contact us by email at [email protected] and let us know the nature of your request and your contact information. We'll do all we can to ensure you're set up for success during our interview process while upholding your privacy, including requests for accommodation.
Salary Context
This $120K-$200K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 2130 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 4,133 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Circuit Check Inc, 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 $185,000 based on 13,200 positions with disclosed compensation. Director-level AI roles across all categories have a median of $250,000. This role's midpoint ($160K) sits 14% below the category median. Disclosed range: $120K to $200K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Circuit Check Inc AI Hiring
Circuit Check Inc has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in San Jose, CA, US. Compensation range: $200K - $200K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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