ZipRecruiter

Log In

1

Afternoon Mechanical Engineering Machine Learning Jobs

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

Engineering, Research & Development Reports to: Metallurgical and Materials R&D Lab Manager ... Background in CFD, simulation, computational mechanics, or applied physics * Familiarity with ...

X4 Engineering

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

Driving engineering best practices across CI/CD, observability, testing, and automation Tech stack ... Machine Learning Engineering ✔ MLOps Engineering ✔ Platform Engineering ✔ Software ...

Apple

Machine Learning Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

Experience in data analysis, data engineering, and machine learning data operations. Experience designing data quality control processes, data curation workflows, or Human-in-the-Loop initiatives.

next page

Showing results 1-20

All JobsAfternoon Mechanical Engineering Machine Learning Jobs

Afternoon Mechanical Engineering Machine Learning information

See salary details

$45.5K

$102.9K

$166.5K

How much do afternoon mechanical engineering machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for afternoon mechanical engineering machine learning in the United States is $102,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,500.00 and $126,500.00 per year, depending on experience, location, and employer.

Can mechanical engineers work in machine learning?

Mechanical engineers can work in machine learning by applying their knowledge of systems, modeling, and data analysis to develop algorithms for automation, robotics, and predictive maintenance. Gaining skills in programming languages like Python, and understanding of data science tools, can facilitate their transition into machine learning roles. Interdisciplinary expertise and additional training in machine learning techniques are often required for such positions.

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

To excel in this role, you need a solid background in mechanical engineering principles, mathematics, and machine learning concepts, usually supported by a relevant engineering degree. Familiarity with technical tools such as Python, MATLAB, CAD software, and machine learning frameworks (like TensorFlow or scikit-learn) is typically required. Strong analytical thinking, problem-solving, and effective teamwork are valuable soft skills for integrating machine learning with mechanical systems. These competencies are crucial for developing innovative solutions and optimizing engineering processes with data-driven approaches.

What is the difference between Afternoon Mechanical Engineering Machine Learning vs Afternoon Mechanical Engineering Data Analysis?

AspectAfternoon Mechanical Engineering Machine LearningAfternoon Mechanical Engineering Data Analysis
Required CredentialsBachelor's or Master's in Mechanical Engineering, proficiency in machine learning toolsBachelor's or Master's in Mechanical Engineering, strong data analysis skills
Work EnvironmentResearch labs, tech companies, manufacturing firmsDesign firms, manufacturing plants, research institutions
Employer & Industry UsageTech-driven engineering sectors applying AI/MLTraditional engineering sectors focusing on data interpretation
Search & Comparison IntentUnderstanding roles involving AI/ML in mechanical engineeringComparing data analysis tasks within mechanical engineering

Afternoon Mechanical Engineering Machine Learning focuses on applying AI and machine learning techniques to mechanical engineering problems, often requiring programming and data modeling skills. In contrast, Afternoon Mechanical Engineering Data Analysis emphasizes interpreting and visualizing data to inform engineering decisions. Both roles share foundational engineering knowledge but differ in their technical focus and application areas.

Will MLE be replaced by AI?

In the context of an Afternoon Mechanical Engineering Machine Learning role, MLE (Machine Learning Engineer) involves designing and deploying models that often complement AI systems. While AI automation can handle certain tasks, MLE professionals are essential for developing, optimizing, and maintaining machine learning solutions, making complete replacement unlikely in the near term. Skills in programming, data analysis, and understanding of algorithms remain critical for MLE roles.

What engineer makes $500,000 a year?

Senior mechanical engineers with extensive experience, specialized skills in machine learning, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large corporations. Achieving this level often requires advanced degrees, certifications, and a strong track record of project success and innovation.

How do mechanical engineers specializing in machine learning typically collaborate with other departments during afternoon shifts?

Mechanical engineers working in machine learning often collaborate closely with data scientists, software developers, and production teams, especially during afternoon shifts when testing and implementation often ramp up. They may participate in cross-functional meetings to align on project goals, troubleshoot issues with live data, and refine machine learning models based on feedback from manufacturing or operations staff. This collaborative environment helps ensure that algorithms are practical, efficient, and aligned with real-world applications. Effective communication and adaptability are key, as priorities can shift rapidly based on production needs.

Can you make $200,000 a year as a mechanical engineer?

Achieving a $200,000 annual salary as a mechanical engineer is possible but typically requires extensive experience, advanced skills in areas like machine learning or automation, and often positions in management or specialized industries such as aerospace or energy. Salaries vary based on location, company size, and individual expertise, with top earners often holding senior or lead roles and possessing professional certifications.

What is an Afternoon Mechanical Engineering Machine Learning job?

An Afternoon Mechanical Engineering Machine Learning job typically refers to a position where professionals apply machine learning techniques to solve problems in mechanical engineering, with working hours scheduled in the afternoon. These roles often involve analyzing engineering data, developing predictive models, and optimizing mechanical systems using advanced algorithms. The work may include tasks such as fault detection, predictive maintenance, or process optimization, leveraging both engineering expertise and machine learning skills. Employees in such positions usually have backgrounds in both mechanical engineering and computer science or data analytics.
More about Afternoon Mechanical Engineering Machine Learning jobs
What cities are hiring for Afternoon Mechanical Engineering Machine Learning jobs? Cities with the most Afternoon Mechanical Engineering Machine Learning job openings:
What are the most commonly searched types of Mechanical Engineering Machine Learning jobs? The most popular types of Mechanical Engineering Machine Learning jobs are:
What states have the most Afternoon Mechanical Engineering Machine Learning jobs? States with the most job openings for Afternoon Mechanical Engineering Machine Learning jobs include:
Afternoon Mechanical Engineering Machine Learning jobs near you

Machine Learning Engineer

Ksb

Grovetown, GA • On-site

Other

Posted 8 days ago

Job description

KSB is a leading supplier of pumps, valves and related service. Our reliable, high-efficiency products are used in applications wherever fluids need to be transported or shut off, covering everything from building services,industry and water transport to waste water treatment, power plant processes and mining. Founded in 1871 in Frankenthal, Germany, the company has a presence on all continents with its own sales and marketing organisations and manufacturing facilities. Around the globe, more than 190 service centres and around 3,500 service specialists are on hand to provide local inspection, servicing, maintenance and repair services under the KSB SupremeServ brand. Innovative technology that is the fruit of KSB's research and development activities forms the basis for the company's success.
People. Passion. Performance. It is these three success factors that make KSB the company it is today.
At KSB, we recognise that it is people who actually make the difference - the people we employ and the people we serve. This is why we are committed to equal rights and treatment worldwide and never lose sight of the aspects ecology and sustainability when manufacturing our products.

Machine Learning Engineer KSB GIW, Inc.

Department: Engineering, Research & Development
Reports to: Metallurgical and Materials R&D Lab Manager
Location: Grovetown, GA, USA (onsite)
Shift: First

FLSA Status: Salary Exempt

OVERVIEW:

Our R&D group is expanding its use of machine learning to solve real engineering problems, and we're looking for a sharp, hands-on early-career engineer to join the team.

You'll work at the intersection of machine learning and the physical world to build AI systems that learn from real industrial data and connect with the engineering models behind them. The role lives where machine learning meets scientific computing: surrogate modeling, data-driven approximations of physical systems, and ML models that respect the underlying engineering principles.

You'll build the data foundation that powers this work, implement and train models that bridge physics-based simulation with modern machine learning, and work closely with an experienced technical lead who will guide your growth across data engineering, scientific ML, and emerging AI tooling.

RESPONSIBILITIES:

  • Build and maintain the data foundation: ingestion, cleaning, transformation, validation, and metadata standards
  • Implement and train machine learning models using Python and modern frameworks (PyTorch)
  • Contribute to applied AI tooling that supports the broader R&D workflow
  • Develop visualization and dashboard interfaces that present results to end users
  • Run experiments, track results, and report findings against defined targets
  • Help bring prototype code to production quality: testing, documentation, version control
  • Collaborate with team members across engineering disciplines

QUALIFICATIONS:

  • Education:Bachelor's degree required; master's preferred in Computer Science, Engineering, Applied Math, Physics, or a related field
  • Experience:1-3 years of professional or substantial project experience in machine learning, data engineering, or scientific computing

SKILLS / COMPETENCIES

Required:
  • Solid Python skills with hands-on experience using core libraries:
    • Machine learning: PyTorch, scikit-learn
    • Data: NumPy, pandas
    • Scientific computing: SciPy, Matplotlib
  • Foundational understanding of scientific computing: numerical methods, simulation concepts, or modeling of physical systems - this is essential to the role
  • Foundational understanding of neural networks, model training, and optimization
  • Experience with version control (Git) and working in a Linux environment
  • Strong written and verbal communication skills
  • Collaborative, coachable attitude
Preferred:
  • Experience building and maintaining data pipelines, metadata schemas, and data quality frameworks
  • Exposure to scientific / physics-informed machine learning (surrogate modeling, embedding physical constraints into ML models)
  • Background in CFD, simulation, computational mechanics, or applied physics
  • Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) enough to collaborate effectively, not lead
  • Experience with Jupyter, Docker, MLflow, or FastAPI
  • Front-end / dashboard development experience (React)
  • Cloud compute (AWS or Azure) and GPU-based training
  • Coursework or research projects in numerical methods, engineering, or applied science

PHYSICAL REQUIREMENTS:

  • Primarily desk-type duty

KSB Group is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. KSB makes hiring decisions based solely on qualifications, merit, and business needs at the time.

We value employees who take the initiative and are committed to our company; Employees who take responsibility and for whom business success is the focus of their actions. In return, we offer fair framework conditions for collective wages and pensions, flexible working time models, individual training opportunities and the best career prospects.

Apply