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Mle Jobs (NOW HIRING)

Ancestry

Machine Learning Engineer, Co-op

The MLE team is responsible for developing, deploying, fine-tuning and optimizing machine learning models and LLMs to enhance customer experiences, improve internal workflows, and drive business ...

NOUS RESEARCH

Machine Learning Engineer

New York, NY · On-site

We're looking for an MLE to scale the training and deployment of large transformer-based models. You'll work across training infrastructure, inference optimization, and reinforcement learning ...

Judge Group, Inc.

Technical Scrum Master

Malvern, PA · Hybrid

$50.50 - $67.50/hr

This team owns all the MLE and ML Ops engineering, development, and implementation for AI Garage models. The candidate must be highly skilled and experienced in scrum practices, including very strong ...

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How much do mle jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for mle in the United States is $26.34, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $30.77 per hour, depending on experience, location, and employer.

Is MLE a good career?

Machine Learning Engineer (MLE) is a growing field with high demand for skills in data analysis, programming, and machine learning frameworks like TensorFlow or PyTorch. It offers competitive salaries, opportunities for innovation, and work in diverse industries such as tech, finance, and healthcare. Success typically requires strong technical skills, continuous learning, and often a background in computer science or related fields.

What is the difference between Mle vs Mechanical Engineer?

AspectMleMechanical Engineer
Required CredentialsTypically requires a degree in data science, computer science, or related fields; certifications in machine learning or AI are commonRequires a degree in mechanical engineering; professional engineering (PE) license may be preferred
Work EnvironmentPrimarily in tech companies, research labs, or AI-focused firms; involves programming and data analysisManufacturing, design firms, or industrial settings; involves design, testing, and manufacturing processes
Employer & Industry UsageUsed in tech, AI, and data-driven industriesUsed in manufacturing, automotive, aerospace, and industrial sectors

While Mle (Machine Learning Engineer) focuses on developing algorithms and models in data science and AI, Mechanical Engineers work on designing and building physical systems and machinery. Both roles require technical skills but differ significantly in their work environment, credentials, and industry applications.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in computer science, mathematics, and statistics, often supported by a relevant degree or equivalent experience. Proficiency with programming languages like Python or R, frameworks such as TensorFlow or PyTorch, and experience with version control and cloud platforms are commonly required. Strong problem-solving abilities, effective communication, and a collaborative mindset are standout soft skills in this role. These skills are vital for building robust machine learning models, translating complex data into actionable insights, and working effectively within multidisciplinary teams.

What are the most common challenges machine learning engineers face when deploying models to production?

Machine learning engineers (MLEs) often encounter challenges such as ensuring model scalability, maintaining performance in real-world data environments, and managing model monitoring post-deployment. Integrating models with existing systems and overcoming data drift or changes in user behavior can also be complex. Collaboration with software engineers and data scientists is crucial to address these issues, as is adopting robust MLOps practices to streamline deployment and monitoring processes.

How much does MLE make?

Machine Learning Engineers (MLEs) typically earn a median annual salary ranging from $100,000 to $150,000, depending on experience, location, and industry. Senior MLEs or those with specialized skills in deep learning or large-scale data systems can earn higher salaries, often exceeding $200,000. Compensation may also include bonuses, stock options, and benefits based on the employer and geographic region.

What engineers make $500,000?

Senior software engineers, especially those in specialized fields like machine learning, data engineering, or software architecture, can earn $500,000 or more annually, often through a combination of base salary, bonuses, and stock options. High compensation is typically associated with experience, advanced skills, working at large tech companies, or in high-demand markets.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, machine learning executive, or senior data scientist, often requiring advanced skills in deep learning, programming, and data analysis. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms.

What are MLEs (Machine Learning Engineers)?

Machine Learning Engineers (MLEs) are professionals who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready applications. MLEs collaborate with data scientists to implement algorithms, manage data pipelines, and optimize the performance of machine learning models. Their role is essential in bringing AI solutions from research to real-world use cases.
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What job categories do people searching Mle jobs look for? The top searched job categories for Mle jobs are:
Mle jobs near you

Senior Process Mechanical Engineer

Consolidated Water Group,

Fountain Valley, CA • On-site

$150K - $180K/yr

Full-time

Posted 23 days ago

Job description


Senior Process Mechanical Engineer – Wastewater Treatment

Location: Fountain Valley, CA (on-site)
Travel: Up to 20–25%

Overview

The Senior Process Mechanical Engineer leads process design for wastewater treatment and advanced water reclamation systems from concept through detailed engineering. This role translates process simulations into practical, constructible designs, including hydraulic profiles, process flow diagrams (PFDs), piping and instrumentation diagrams (P&IDs), equipment selection, and facility layouts.

This position requires expertise in biological treatment systems and advanced membrane technologies and plays a key role in delivering high-performance, sustainable water infrastructure solutions.

Key Responsibilities

Process Engineering & Design

  • Lead process design from conceptual phase through Issued for Construction (IFC).

  • Perform process simulations using tools such as BioWin or equivalent.

  • Design biological treatment systems including MBR, MBBR, SBR, IFAS, MLE, Bardenpho, and oxidation ditch processes.

  • Develop hydraulic profiles, PFDs, and P&IDs.

  • Conduct process calculations, mass balances, and system performance evaluations.

Advanced Treatment Systems

  • Design and integrate advanced treatment technologies including MF/UF, NF, RO, and AOP.

  • Develop treatment trains for water reuse and advanced reclamation.

  • Perform membrane sizing, recovery analysis, and fouling evaluations.

Equipment & Facility Design

  • Lead equipment sizing and selection (pumps, blowers, reactors, membrane systems, chemical dosing systems).

  • Develop and review plant layouts and general arrangement drawings.

  • Ensure efficient process flow, constructability, and maintainability.

Project Delivery

  • Manage deliverables through all phases (Conceptual, 30%, 60%, 90%, IFC).

  • Ensure designs meet schedule, budget, and quality requirements.

  • Lead design reviews and support commissioning and startup activities.

Multidisciplinary Coordination

  • Coordinate with mechanical, civil, structural, electrical, instrumentation, and CAD teams.

  • Provide input on controls, automation, and system integration.

  • Resolve design conflicts and ensure coordinated deliverables.

Technical Leadership

  • Mentor junior engineers and review technical work products.

  • Contribute to engineering standards and best practices.

  • Serve as a subject matter expert in wastewater treatment and water reuse systems.

Business Development Support

  • Support technical proposals, design narratives, and preliminary cost inputs.

  • Participate in client meetings and technical presentations.

  • Assist in evaluating project feasibility and technical risks.

Qualifications

Required Experience

  • 10–15 years of experience in wastewater treatment and water reclamation design.

  • Experience with process modeling and simulation (BioWin preferred).

  • Extensive experience in biological treatment systems (ASP/BNR, MBR, MBBR, SBR, IFAS, MLE, Bardenpho) and advanced treatment technologies (MF/UF, NF, RO, AOP).

  • Proven ability to deliver projects from concept through IFC.

  • Strong knowledge of applicable standards (AWWA, ASME, ANSI, WEF).

  • Experience coordinating multidisciplinary teams.

Education & Certifications

  • Bachelor’s degree in Chemical, Environmental, Mechanical, or Civil Engineering (or related field).

  • Professional Engineer (PE) license preferred (California strongly preferred).

  • Additional training in process modeling software is a plus.

Work Environment & Physical Requirements

  • Combination of office and field work environments.

  • Ability to travel up to 20–25% for site visits and client meetings.

  • Ability to occasionally lift up to 30 lbs.

  • Use of personal protective equipment (PPE) may be required in field environments.