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Machine Learning Engineer Opt Jobs in Austin, TX

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI-enabled solutions that improve software delivery workflows, automate operational processes, and ...

About the Role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

About the Role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

Machine Learning Engineer

Austin, TX · On-site

$132K - $244K/yr

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

PayPal, Inc. seeks Machine Learning Engineer in Austin, TX Job Duties: Gather, analyze and implement high-impact statistical models and AI applications in various business functional areas, focusing ...

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Machine Learning Engineer Opt information

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$31.2K

$127.6K

$191.8K

How much do machine learning engineer opt jobs pay per year?

As of Jun 18, 2026, the average yearly pay for machine learning engineer opt in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

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 mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
What job categories do people searching Machine Learning Engineer Opt jobs in Austin, TX look for? The top searched job categories for Machine Learning Engineer Opt jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Engineer Opt jobs? Cities near Austin, TX with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer

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Retirement

Posted 15 days ago


Job description

Machine Learning Engineer (Austin, TX)

Striveworks is a leader in Machine Learning Operations for highly regulated industries such as the Department of Defense/U.S. Military. They enable their customers to extract actionable insight from their data at the point of collection and indefinitely in the future with the help of AI/Machine Learning. The product they offer allows their clients to monitor, manage, integrate, visualize, export, and analyze their data to inform decisions and streamline business.

They are looking to double the team that they have currently of about 60 employees over the next year. They are a startup, and this is a very unique opportunity to join their team in their fastest growing stages.

Location: Austin, TX

Salary: 140K-190K

Bonus: annual and performance based

401K Match: n/a

Benefits: Equity - Owners have a history of another startup that turned to IPO in 5 years. The company offers a generous equity plan to be a stakeholder and participate in the company's success.

Position Summary

As a Machine Learning Engineer on the Striveworks Technical Engagements team, you'll be challenged - and trusted - on day one to be a core contributor to the projects and direction of the company. You will be a key representative and solutions provider to sites and customers where Striveworks' proprietary data platform is deployed.

You will integrate and apply this platform, and rapidly prototype and deliver machine learning capabilities for customers. You'll tackle real world problems as they unfold, utilizing your technical and communication skills to provide reliable and scalable solutions.

At times, you will be tasked with on-site travel to customer locations. At other times, you will be based in Striveworks' Austin, TX headquarters.

Requirements

-Able and willing to travel domestically and internationally up to 10%

-B.S. Degree in Computer Science, Machine Learning, or Related disciplines; and 2+ years of relevant experience

-Excellence in Python

-Deep expertise in algorithms and data structures

-Exposure to DevOps tooling and best practices (Git, Docker, Kubernetes, CI/CD tools)

-Familiarity with relational and non-relational database design and architecture

-Familiarity with Javascript

Nice To Haves

-Experience with ETL/data pipelines

-Understanding of JavaScript frameworks (React, Vue, or Angular)

-Experience designing RESTful or GraphQL APIs

-Comfortable with Cloud Architecture

-Tensorflow/PyTorch experience

-Knowledge of messaging systems like Kafka, RabbitMQ, or similar

-GoLang/Flyte experience


1872 Consulting logo

About 1872 Consulting

Sourced by ZipRecruiter

1872 Consulting, based in Chicago, IL, USA, operates within the IT consulting industry. Armed with a diverse team of experts, the company offers specialized IT consulting services, focusing on modernizing business technologies and driving innovative business strategies. Established in 1872, the company has a rich history marked by its commitment to bridging the gap between businesses and technology. Its mission is to empower organizations to surpass their business goals by providing state-of-the-art IT solutions and service. The company prides itself on its core values of integrity, excellence, and innovation, instilling these principles in every project they undertake.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

Chicago, IL, US

Year founded

2014