AI is changing industries fast, and as a Machine Learning Engineer, knowing your market value is key to career growth. In the US, the average salary for ML engineers is $172,481 per year, with earnings ranging from $103,688 to $286,914. Navigating this range takes more than skills or experience. It’s about showing your unique impact in a competitive field.

This guide breaks down salary expectations for 2025, helping you gauge your worth and negotiate better pay. Whether you’re just starting out or have years in the game, let’s explore how to boost your earning potential with clear strategies and data-driven insights.

Want to know where you stand? Get a free career plan and skill assessment to see your position in today’s market and uncover steps to grow faster.

How Machine Learning Engineer Salaries Are Changing

What Makes 2025 Salaries Different for ML Engineers

In 2025, ML engineer salaries reflect a shifting landscape with new opportunities and hurdles. As AI reshapes business needs, your value as an engineer isn’t just about coding. It’s about solving real problems and driving measurable results.

Old-school performance reviews often miss the mark for modern ML roles. With AI handling routine tasks, standing out requires more than technical output. Companies now value engineers who can use AI tools effectively and show direct impact on business goals.

This gap between your contributions and how they’re recognized can leave you unsure of your worth. Many managers, pressed for time, offer vague feedback, making it hard to understand your market value or next steps. That’s where a clear strategy can help.

Latest Trends in the ML Job Market

The ML job market in 2025 shows high demand but tougher expectations. Businesses across sectors rely on AI, creating a need for skilled engineers. However, employers want more than coding ability. They seek professionals who connect technical work to business outcomes.

Salaries mirror this shift. Entry-level ML engineers with under a year of experience earn about $96,095 annually, while those with 5-9 years average $143,641 per year. Experience and proven results clearly drive higher pay.

Technology moves fast, so skills can outdated quickly while new areas emerge. If you adapt, keep learning, and communicate your value, you’re more likely to reach top salary brackets in this ever-changing market.

Understanding ML Engineer Pay: More Than Just Base Salary

Breaking Down Your Compensation Package

Your pay as an ML engineer includes more than just a base salary. A full package can greatly increase your total earnings and long-term financial growth.

Base salary is the starting point, but bonuses, equity like stock options or RSUs, and benefits add significant value. Extra cash compensation averages $44,280 yearly, pushing median total pay to $202,427 when everything’s accounted for.

Benefits now often cover remote work options, learning stipends, wellness programs, and performance rewards. Many AI firms offer budgets for ongoing education, knowing that staying current with tech is vital for everyone involved.

Equity can be a big deal, especially with growing AI companies. Evaluating vesting schedules, strike prices, and the company’s future potential is crucial to understanding your full earning power.

Typical Salary Ranges for ML Engineers

Knowing typical salary ranges helps set realistic expectations, but data varies based on source, location, and company type. Let’s look at some current figures.

PayScale pegs the average ML engineer salary at $122,630 for 2025, with entry-level roles at $102,174 and early-career engineers around $121,367. These numbers focus on base pay, not the whole package.

Total compensation, including bonuses and benefits, often looks better. Leading tech giants and AI firms tend to pay at the higher end, especially for critical roles. Pay also shifts based on where you work. In tech hubs like San Francisco, salaries average $134,901, and in New York City, they’re around $127,759, though living costs play a role.

Factors That Shape Your ML Engineer Salary

How Experience Impacts Pay From Entry-Level to Senior Roles

Your experience level heavily influences your salary, but in 2025, it’s not just about years worked. Showing real impact can fast-track your earnings.

Salary growth follows clear steps. Engineers with 1-4 years of experience earn about $112,962 yearly, while those with 5-9 years average $143,641. The jump early on shows how quickly proven skills pay off.

Years alone aren’t enough anymore. If you can lead projects, solve key problems, and link your work to business results, you’ll often outpace standard salary ranges based on tenure.

For senior or principal roles, pay climbs higher. But getting there means showing leadership, strategic thinking, and the ability to guide teams or set technical direction, not just logging more time.

Where You Work and How It Affects Pay

Location still plays a big role in salary differences for ML engineers, though remote work is changing the game. Tech hubs offer higher pay, but options are expanding.

Cities like San Francisco, Seattle, New York, and Boston lead with above-average salaries due to the cluster of AI firms and competition for talent. These areas benefit from heavy investment and high AI adoption, pushing pay upward.

Remote work opens doors to solid pay no matter where you live. Many companies adjust salaries based on location, but you can still earn competitively in lower-cost areas, balancing income with living expenses.

Globally, the US market remains ahead with stronger salaries, equity options, and growth paths compared to other regions, adding to long-term financial benefits.

Skills and Specializations That Boost Pay

Certain skills and focus areas in machine learning can directly increase your earning potential by matching market needs. Knowing what’s in demand helps you prioritize.

Basic skills like Python, TensorFlow, PyTorch, and cloud platforms are expected. But specializing in areas like Natural Language Processing, Computer Vision, or MLOps can lead to higher pay due to their business applications and smaller talent pools.

New fields like AI safety, ethics, and responsible AI development are gaining traction as firms focus on compliant systems. Combining technical know-how with regulatory awareness sets you up for better compensation.

Expertise in large language models, retrieval-augmented generation, or building production-ready AI apps is highly sought after. If you can show strength in these areas, you’ll have stronger leverage in salary talks.

Company Size and Type: Startup vs. Tech Giant Pay

The type and size of your employer shape your pay package, each with distinct pros and cons for both short-term income and career path.

Large tech giants like FAANG companies often provide competitive total pay, especially for senior roles. This includes solid base salaries, bonuses, equity, and benefits that can boost your future opportunities, though specifics depend on your position and team.

Startups might offer lower base pay but bigger equity stakes. Early-stage ones carry higher risk but potential for huge returns, while later-stage startups balance risk with more stable packages.

Mid-size firms often fall in between, with decent base pay and moderate equity. They can offer better work-life balance, direct impact on products, and clearer routes to leadership roles.

Does Education Level Change Your Salary?

Your education, especially advanced degrees, can influence pay, but the effect depends on your career stage and how you apply your knowledge.

A Master’s degree in fields like Computer Science or Data Science often boosts pay for newer engineers. The deep learning and research background help you start strong and adapt quickly, which employers value.

A PhD can mean higher starting pay and access to niche research roles. But the time spent studying versus gaining work experience is a trade-off. Often, real-world impact weighs as much as or more than formal education.

Alternative paths like bootcamps or self-learning are gaining ground. Many employers now prioritize skills and project portfolios over traditional degrees, especially for seasoned engineers.

Showing Leadership and Value to Increase Pay

Moving into leadership roles or proving your impact can significantly raise your salary. These steps show you’re more than a technical contributor.

Skills in guiding projects, mentoring others, and shaping technical strategy are highly valued as teams grow and challenges get complex. If you balance hands-on work with bigger-picture thinking, you’re in demand for higher-paying roles.

Proving business impact is key. If you can show how your work drives user growth, cuts costs, or boosts revenue, you build a strong case for better pay.

Bridging tech and business needs sets you apart. Engineers who speak to stakeholders, turn goals into solutions, and highlight returns on investment often break through typical salary limits.

Steps to Increase Your ML Engineer Salary

Use Data to Tell Your Impact Story

Standing out in today’s market means showing your value with hard numbers, not just listing skills or projects. Data makes your case stronger.

Instead of saying you built a system, detail the outcome. For example, “I created a recommendation system that raised user engagement by 23% and added $2.4 million in yearly revenue.” Specific results speak louder.

The trick is tracking your work’s effects over time. Build a record linking your efforts to business wins. This portfolio of results shows your growth and influence clearly.

Frame your story to include team or company success. Highlight how your work fits into larger goals while taking credit for your unique role in those wins.

Leverage AI to Raise Your Impact

AI isn’t just a challenge, it’s a tool to boost your output as an ML engineer. Using it well can position you for higher pay.

Learn to work with AI to speed up development, improve code, and solve problems faster. Showing you can produce more with these tools makes you a key player in any organization.

Instead of fearing automation, use it to enhance your creativity. Focus on what needs human insight and combine it with AI for the best results.

Stay updated on AI tools and trends. If you can adopt and optimize these systems for your team, you’ll often land leadership roles with better compensation.

Keep Learning Skills That Matter

Staying competitive means learning strategically, focusing on skills that match market needs and your career goals, not just learning for the sake of it.

Top engineers balance core skills with niche expertise. You might specialize in computer vision while keeping broad ML knowledge, or focus on MLOps to link research with real-world use.

Learning only pays off if you apply it. Turn new skills into visible value for your company. This shows you’re not just gaining knowledge, but using it effectively.

Don’t stop at technical skills. Understanding cloud systems, business metrics, and clear communication all help you deliver more impact and justify higher pay.

Find Your Market Value with Exceeds.ai

Knowing your worth goes beyond looking at average salaries. It’s about your unique skills, experience, and impact, which standard benchmarks often miss.

Exceeds.ai offers tailored career paths to guide your growth. It evaluates your skills and background to pinpoint opportunities and next steps for advancement.

Through code-based analysis, the platform gives clear feedback on your technical strengths and areas to improve, focusing on quality and scalability as you work.

With its Proof of Impact feature, Exceeds.ai tracks your achievements over time, creating a solid record for reviews or negotiations. This data backs up your value.

The tool also provides pay insights based on your specific abilities, using public data enhanced by AI. This helps you negotiate with confidence. Ready to see your true worth? Get a free career plan and skill assessment from Exceeds.ai now.

How to Negotiate a Better ML Engineer Salary

Do Your Homework Beyond Basic Data

Successful salary talks start with thorough prep, not just glancing at public pay stats. Your unique value and the company’s structure matter most.

Internal pay scales and promotion rules often differ from online data. Learn how your employer sets levels and evaluates growth by connecting with mentors and observing patterns.

Assess the company’s financial health and priorities. Align your request with their goals and timing for a stronger case during negotiations.

Build a detailed argument with market data plus proof of your impact. Document your wins and show how you’re an asset to the company’s future.

Present Your Value Clearly

How you share your contributions can make or break a negotiation. It’s about connecting your work to results in a way that clicks with decision-makers.

Go beyond listing tasks. Tell stories that mix hard data with insights into your approach, leadership, and team impact for a compelling pitch.

Confidence comes from preparation. Speak to specific achievements with examples and numbers. This credibility supports your case for better pay while staying professional.

Frame your request as a win-win. Show how fair pay reflects your ability to bring even more value, making it an investment, not just a demand.

Pick the Right Moment and Approach

Timing can sway negotiation results. Choose moments when you have leverage and the company can act favorably.

Reviews, project wins, or budget seasons are ideal for talks. Major contributions or outside offers can also justify discussions outside normal cycles if you show immediate value.

Present a full proposal, not just a number. Research similar roles, outline scenarios for pay or growth, and consider non-monetary perks of equal worth.

Having real alternatives, like other offers, strengthens your position. But be ready to follow through if talks don’t meet your expectations.

Avoid Common Negotiation Mistakes

Even skilled engineers slip up in talks. Steering clear of these errors can improve your outcomes and keep relationships intact.

Don’t base requests on personal needs. Focus on market value and impact, since companies prioritize business outcomes over individual situations.

Not measuring your impact weakens your case. Specific results carry more weight than vague claims about your work.

Accepting first offers without review often leaves money behind. Most firms expect negotiation and build room into initial proposals. Look at the full package.

Keep talks collaborative, not confrontational. A professional tone preserves goodwill for future opportunities, even if results aren’t ideal.

Use Exceeds.ai to Negotiate Smarter

Data and preparation elevate salary talks, and Exceeds.ai supports this with tools to strengthen your approach as an engineer.

The Proof of Impact feature captures your achievements, giving hard evidence for pay requests. This record is key to showing your worth.

Exceeds.ai refines public pay data with insights on your skills and position, offering tailored benchmarks for more effective talks.

Through Skill Radar and code insights, the platform builds confidence by validating your strengths and business impact, helping you negotiate convincingly. Ready for better talks? Get a free career plan and skill assessment to prepare with solid data.

Common Questions About ML Engineer Salaries

Are ML Engineer Salaries Really Growing?

ML engineer salaries are rising beyond just inflation, fueled by market demand. AI’s growing role in business drives need for skilled professionals, while the specialized talent pool stays limited.

This growth stems from high business value in AI projects, often outweighing engineer costs. Plus, experienced engineers who tackle complex challenges remain rare, justifying higher pay.

Salaries also reflect the shift to strategic roles. If you link tech work to business wins, you’re often rewarded with stronger compensation.

Growth isn’t equal across roles. Entry-level pay rises slowly with more graduates, but seasoned engineers with proven impact see sharper increases.

How Much Does Location Affect Pay?

Location impacts ML engineer pay significantly, though remote work is reshaping this. Tech hubs like San Francisco, Seattle, and New York pay 20-40% above national averages due to company density and living costs.

A $180,000 salary in San Francisco might match $130,000 in Austin when adjusted for expenses, so raw numbers don’t tell the whole story.

Remote roles now offer competitive pay with slight geographic adjustments, often 80-95% of hub rates. This broadens access to good salaries.

US salaries still outpace global markets. International roles require weighing taxes, healthcare, and growth options alongside base pay.

Do Advanced Degrees Raise My Salary?

Advanced degrees can increase pay, but the boost depends on career stage and application. Their value is less straightforward as experience grows.

A Master’s often helps early on, offering 10-20% more than a Bachelor’s due to deeper training. It aids quick adaptation, which employers appreciate.

A PhD can lead to higher starting pay or research roles, but lost work years are a factor. Early career entry might match or exceed this over time.

Degrees matter most when paired with real-world impact. Applying theoretical skills to solve problems maximizes financial returns from education.

How Do I Prove Value When AI Automates Tasks?

Showing value in an AI-driven field means focusing on impact, not just tasks. Use automation as a tool to highlight your strategic role.

Track and document business outcomes from your work, like user growth or cost savings. These numbers build a clear case for higher pay.

Emphasize skills AI can’t replicate, like system design or team guidance. Positioning yourself as a bridge between tech and business needs makes you essential.

Communicate in business terms. Explain not just what you did, but why it mattered and how it helped the company succeed. This skill drives pay and growth.

Can Exceeds.ai Assess My Unique Skills for Pay?

Exceeds.ai evaluates your worth by analyzing real contributions, like GitHub code, not just surveys. This approach captures your specific value beyond generic data.

It reviews your work for technical strengths in quality and scalability. Features like Code-Based Skill Insights offer clear feedback on where you shine or need growth.

The platform tailors pay benchmarks to your skills using public data and AI insights, giving a more accurate view of your market position.

Assessments update as you grow, ensuring advice matches your current abilities and guides ongoing career and pay strategies.

Take Charge of Your ML Engineer Career in 2025

Earning what you’re worth as an ML engineer in 2025 takes more than technical skills. It requires strategy, active career planning, and clear proof of your impact in a fast-moving field. Engineers who secure top pay show results, use AI smartly, and tell strong stories about their value.

With average salaries at $172,481 and total pay often over $200,000 for experienced roles, there’s real opportunity. But reaching these levels means understanding pay drivers and mastering negotiation.

Focus on proving impact with data over just experience or credentials. Success comes from measuring results, sharing your value, and positioning as a key contributor, not just a coder.

Exceeds.ai can help with tailored career paths, skill feedback via Skill Radar, and impact tracking through Proof of Impact. It’s like having an AI career coach to build skills and push growth.

Don’t let outdated reviews or limited feedback hold you back. With the right approach, you can shape your path, prove your worth, and earn what matches your contributions.

Ready to take control? Get a free career plan and skill assessment with Exceeds.ai to build a data-driven case for your next promotion or dream role.

The future favors engineers who adapt and show confidence in a changing market. Your pay reflects not just skills, but how you prove impact and plan for growth. Start maximizing your potential today.