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Applied Machine Learning Jobs (NOW HIRING)

Apex Informatics

Machine Learning Engineer

Applied Machine Learning Engineer | Music Software (Multiple Roles open) Role: Applied Machine Learning Engineer (Mid - Senior Opportunity) Company: Splash Employment Type: Contract (3 months ...

Apex Informatics

Applied Machine Learning Engineer

A strong focus on applied problem-solving, with a practical approach to integrating existing tools and systems. * A good understanding of music, production, or audio technology processes (or a strong ...

StackAdapt

We are searching for a talented Senior/Staff Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands ...

Apple

Sr. Machine Learning Engineer

Santa Clara, CA · On-site

$143K - $189K/yr

As an Applied ML team, we are pushing the boundaries to provide our users with the utmost optimal ... Our team comprises a diverse range of backgrounds, including applied machine learning engineers ...

Respondology

Senior Applied Machine Learning Engineer

$140K - $175K/yr

About the role: We're hiring a Senior Applied Machine Learning Engineer to join the small team that makes AI work tractable, safe, and fast across the company. In this role, you'll ship LLM-powered ...

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Applied Machine Learning information

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$25.5K

$42.6K

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How much do applied machine learning jobs pay per year?

As of Jul 21, 2026, the average yearly pay for applied machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the typical collaboration dynamics between Applied Machine Learning engineers and other teams within a company?

Applied Machine Learning engineers often work closely with cross-functional teams including data scientists, software engineers, product managers, and business analysts. They are typically responsible for translating business problems into machine learning solutions and ensuring models are effectively integrated into production systems. This role requires frequent communication to align on project goals, share progress, and address technical challenges, making teamwork and stakeholder management crucial for successful deployments and continuous improvement.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms. Compensation at this level reflects significant expertise, responsibility, and impact on business or product development.

What is applied machine learning?

Applied machine learning involves using machine learning techniques and algorithms to solve real-world problems in various industries, such as healthcare, finance, and technology. Practitioners focus on selecting appropriate models, preparing data, training algorithms, and deploying solutions that deliver tangible value. Unlike theoretical machine learning, applied machine learning emphasizes practical implementation, evaluation, and optimization to meet business or research objectives.

Is applied AI a good career?

Applied machine learning is a growing field with strong demand for professionals skilled in algorithms, programming, and data analysis. It offers opportunities in various industries such as technology, healthcare, and finance, often requiring knowledge of tools like Python, TensorFlow, and cloud platforms. The career can be rewarding with continuous learning and development of specialized skills.

What are the key skills and qualifications needed to thrive as an Applied Machine Learning professional, and why are they important?

To excel in Applied Machine Learning, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a relevant degree or certification. Familiarity with programming languages like Python or R, frameworks such as TensorFlow or PyTorch, and version control systems is typically required. Strong problem-solving abilities, communication skills, and a collaborative mindset help you interpret results and convey insights to diverse stakeholders. These competencies are crucial for building effective models, driving data-driven decisions, and ensuring the successful integration of machine learning solutions into real-world applications.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries or companies can earn $500,000 or more annually. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of successful projects in applied machine learning environments.

Will MLE be replaced by AI?

Applied Machine Learning (MLE) professionals design, develop, and implement machine learning models, which are essential for AI systems. While AI automation tools can assist or streamline certain tasks, MLE roles focus on model development, data preprocessing, and system integration that require specialized expertise, making complete replacement unlikely in the near term.
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What cities are hiring for Applied Machine Learning jobs? Cities with the most Applied Machine Learning job openings:
What are the most commonly searched types of Applied Machine Learning jobs? The most popular types of Applied Machine Learning jobs are:
What states have the most Applied Machine Learning jobs? States with the most job openings for Applied Machine Learning jobs include:
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Applied Machine Learning jobs near you
Infographic showing various Applied Machine Learning job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Senior Applied Machine Learning Engineer

Hewlett Packard Enterprise Development LP

Fort Collins, CO • On-site

$103K - $142K/yr

Full-time

Posted 6 days ago

New

Job description

Senior Applied Machine Learning EngineerThis role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.Our culture thrives onfinding new and better ways to accelerate what's next.We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs.We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you.Open up opportunities with HPE.

Job Description:

We are seeking an experienced Senior Applied Machine Learning Engineer with a proven track record of deploying, integrating, and leveraging machine learning and AI solutions in real-world, customer-facing environments. The ideal candidate has worked either directly with clients as part of an AI/ML solutions team or as an end-user of AI/ML products to solve practical business challenges.

Role Overview:
In this role, you will apply your hands-on experience with machine learning and AI technologies to build, optimize, and integrate solutions that address customer needs and improve product performance. You will translate complex data and AI/ML models into accessible, scalable solutions, working closely with cross-functional teams to ensure successful deployment and adoption.

Responsibilities:

Applied ML Development:

  • Design, develop, and deploy machine learning models and AI solutions that address real-world customer problems, focusing on usability, scalability, and performance.

Proof of Concept & Innovation:

  • Rapidly develop demos, POCs, MVPs, and workflows to showcase new AI/ML capabilities that could be integrated into the product or used to improve existing features based on customer feedback or market research. Work in a fast-paced environment to experiment with emerging techniques and tools, ensuring the creation of tangible, functional prototypes that demonstrate practical AI/ML solutions for real-world problems.

Integration & Deployment:

  • Develop and improve integrations of open-source ML/AI tools (e.g., MLFlow, Spark, LangChain, Kubeflow) within production environments, ensuring seamless operation on platforms like Kubernetes.

Solution Optimization:

  • Fine-tune models and algorithms for accuracy, efficiency, and scalability in production settings, including deep learning technologies.

Product & System Enhancement:

  • Translate customer requirements and industry trends into actionable AI/ML solutions that improve product features, data management, and system performance.

Collaboration & Communication:

  • Work closely with product managers, data scientists, and engineering teams to brainstorm, design, and deploy AI/ML solutions, documenting procedures and best practices.

Leadership & Advocacy:

  • Lead efforts in integrating emerging AI tools, mentor junior team members, and communicate progress and challenges to leadership.

Must Have:

  • PhD with at least 2 years of relevant industry experience, or the equivalent (e.g., Master's degree with 4+ years, Bachelor's with 6+ years).

  • Extensive hands-on experience applying machine learning and AI solutions in customer-facing or end-user environments.

  • Proven ability to deploy models in production, ensuring reliability and performance.

  • Experience with open-source ML/AI tools and frameworks.

  • Experience with backend programming languages (Python, Go).

  • Proficiency in developing, using, and maintaining AI agents; proven experience coding agents for automation or decision-making tasks.

  • Excellent written and verbal communication skills, especially in asynchronous collaboration.

Nice to Have:

  • Experience with AI agents and automation.

  • Knowledge of inference deployment and optimization techniques.

  • Familiarity with large-scale data pipelines.

  • Experience with retrieval-augmented systems (e.g., RAG).

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#unitedstates

Job:

Engineering

Job Level:

TCP_04"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 144,000 - 273,000 in Colorado // 155,500 - 315,000 in California // 137,000 - 315,000 in Texas
The listed salary range reflects base salary. Variable incentives may also be offered."

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

The estimated job application period closure is September 1 2026; this timeline is provided for transparency and internal planning purposes.

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual's own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.

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