Machine Learning Engineer and Scientist Job Market Trends August 2024-January 2025
Machine Learning Engineer and Scientist salary, skills and job trends are something many are curious about as the demand for AI tools, stocks and strategies has been rapidly increasing and shows no hint of slowing down. As we move further into 2025, the job market for machine learning (ML) professionals continues to evolve rapidly. Companies are increasingly recognizing the transformative potential of ML, leading to heightened demand for skilled workers in this field. Here are some key trends (from our analysis of job postings) defining the landscape of machine learning engineer and scientist jobs across the last six months (August 2024 – January 2025).
Summary of Key Insights:
Job Postings
ML engineer and scientist jobs increased 32% in January compared to December. January postings were relatively flat showing a 2.2% decrease from August 2024. October and November saw the largest blips in postings. Reposting rate decreased 35% in January.
Across the last six months we see the total number of postings for ML engineers and scientists in the table below. The urgent indicator for ML engineering jobs was only used in .03% of job postings and 9.43% of these jobs were sponsored.
In the table below we can see the top 20 companies sorted by the number of postings over the last six months. Apple, Outlier AI and Google top the list.
The top 20 markets for ML job postings are below. San Jose, Seattle and New York top the list. Smaller markets include Columbus and Pittsburgh.
Compensation
We segment comp market analysis into three groups – minimum, middle and maximum and display the average of each group over the time period. Then we calculate the difference between the maximum and minimum groups for the range metric so you can see how wide or narrow of a range is being advertised. Below you can see the differences in comp between ML engineer and scientist jobs. The average min comp is $137,444, mid comp is $175,709 and max comp is $213,973.
January comp was pretty flat compared to December, but trending upwards by at least 6% across the comp groupings compared to six months ago.
Sorted by companies with the highest posting volume that advertise comp we see the top 20 companies below and their comp grouping averages. Pearson has the lowest range % in this list, or the most narrow spread of comp ranges it advertises. A lower range % gives job seekers a more true picture of the comp offering for the advertised position.
Below we see the top 20 companies sorted by their mid-comp grouping average. The companies with higher comp have fewer postings.
Top markets are sorted by mid comp below. As you would expect the larger markets with more postings have higher average mid comp. Austin and Baltimore are mid size markets that made the top 20 list and have at least 20 postings over the last six months.
Fill Days
Average fill days across six months is 37.4, however January saw the shortest amount of time at 24 days, which was a 48% decline from December.
Remote Work Status
Software related jobs still remain one of the professions that can work remotely and this trend continues in the machine learning sector. This will help fill roles that have specialized skills. Below we see remote work status from postings over the last six months. Some type of remote work arrangement was offered in 14% of job postings. January saw an uptick in remote compared to December.
Increased Demand for Specialized Skills
The ML landscape is diversifying, with companies seeking professionals who possess specialized skills in areas such as natural language processing (NLP), computer vision, and reinforcement learning. As industries leverage these advanced techniques, ML practitioners with expertise in specific domains are particularly sought after.
Understanding how to collect, clean, and manage data is becoming crucial. As a result, roles that intersect machine learning and data engineering are gaining popularity. Professionals who can bridge the gap between data science and engineering will be at an advantage, allowing organizations to process data more effectively for model training.
Machine Learning Engineer and Scientist Skills Trends
Top desired skills for machine learning engineers and scientists analyzed across job postings from August 2024 through January 2025 are included in the graph below.
The top five advertised desired skills for jobs include: Machine Learning, Python, AI, PyTorch, and Tensorflow. Communication skills were also important.
Below we take a closer look at few of the employers advertising the most machine learning engineer and scientists jobs. We can see how the desired skills vary by Apple, Google and Amazon.
Apple – Advertised Job Skills
Apple had 890 job ads over this time frame and the key job skills were: Machine Learning, Python, PyTorch, Computer Science and AI.
Google – Advertised Job Skills
Google had 151 job ads over this time frame and the key job skills were: Machine Learning, AI, Natural Language Processing, Software Development and Distributed Systems.
Amazon – Advertised Job Skills
Amazon had 107 job ads over this time frame and the key job skills were: Machine Learning, SDLC, Design Patterns, Computer Science, AWS.
Seniority Level
The majority of employers are looking for senior level ML engineers/scientists. Followed by mid level and then workers with three years of experience. Although in November there was a spike in entry level job postings.
Certifications and Continuous Learning
As the ML field evolves, continuous learning has become imperative. Professionals are encouraged to pursue ongoing education through online courses, certifications, workshops, and conferences to stay competitive. Companies are also investing in training programs to upskill their employees. Some of the top certifications advertised in job postings include: ML fundamentals, AWS, CompTIA Security and PMP.
Emerging Job Titles
New job titles are emerging in the ML space, reflecting the increasing specialization of roles. Positions such as ML Ops Engineer, AI Product Manager, and Data Storyteller are becoming common, indicating a shift in how organizations are structuring their teams around machine learning initiatives.
Conclusion
The job market for machine learning professionals in 2025 is vibrant and full of opportunities. With the right skills and a focus on continuous learning, there are numerous avenues for career advancement. As industries continue to embrace the power of machine learning, the demand for talented professionals in this field is only expected to grow.
By staying informed of these trends recruitment professionals can improve their strategies.
Data sources: Indeed, Linked In
Try Our Free Version of TalentView to Get Instant Talent Market Insights on Postings, Comp and Fill Days (No Sign Up Required)
What is TalentView?
Public Insight develops TalentView, a talent market intelligence solution that generated these insights. The most current and detailed insights are available by title, employer, location, industry and more. We provide flexible ways to utilize talent market intelligence, which include interactive dashboards, reports and data integration.
How Can Our Must-Have Insights Help You?
- Inform/Justify Recruiting Decisions and Prepare For Hiring Manager Discussions
- Inform Recruitment Marketing Budgets, Strategies and Priorities
- Benchmark Employers Against Competitors (local and industry)
- Identify Business Development Opportunities (for Solution Providers)
- Integrate Talent Market Data to Enhance Your Offering (for Solution Providers)
Schedule a Call – Let us demonstrate how you can leverage comp and talent market insights.
Sign Up for a Trial – Try out our interactive dashboards or get sample data for proof of concept.
