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Machine Learning Engineer Jobs in Austin, TX (NOW HIRING)

AI/ Machine Learning Engineer

Austin, TX

$96K - $132K/yr

Mid-Level AI/Machine Learning Engineer Join one of the top 10 global powerhouses transforming the future of Market. As an AI / Machine Learning Engineer, you'll play a key role in designing ...

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 ...

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

Currently, we are looking for entry-level software programmers, IT enthusiasts, Python/Java ... NLP, Deep Learning, Data visualization, Scala, Django Our candidates always get projects with well ...

Senior Machine Learning Engineer

Austin, TX

$103K - $142K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121K - $160K/yr

The Role As a Senior Machine Learning Engineer at Striveworks, you'll be challenged-and trusted-on day one to be a core contributor to both the customer-driven projects and the enduring products of ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

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

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

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Machine Learning Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

How much do machine learning engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for machine learning engineer 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.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

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 technology 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 do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers 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 solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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 strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Austin, TX? The most popular types of Machine Learning Engineer jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Engineer jobs? Cities near Austin, TX with the most Machine Learning Engineer job openings:

AI/ Machine Learning Engineer

Cogent Info

Austin, TX

$96K - $132K/yr

Other

Posted 15 days ago


Job description

Mid-Level AI/Machine Learning Engineer

Join one of the top 10 global powerhouses transforming the future of Market. As an AI / Machine Learning Engineer, you'll play a key role in designing, developing, and deploying intelligent systems that support millions of users worldwide. From building scalable machine learning models and data pipelines to deploying AI solutions on cloud platforms, this is your opportunity to make a global impact with next-generation, data-driven systems. Whether you're a model builder, problem-solver, or technical leader, this team values engineers who bring innovation, collaboration, and a passion for applying AI at scale.

Location: flexible to relocate nationwide / relocate in particular time zone Full-time on-site required

Build Intelligent Systems That Make an Impact!

We're looking for mid-level AI professionals (3–7 years' experience) who are passionate about building, deploying and scaling AI and Generative AI solutions in production environments.

Open Roles
  • Machine Learning Engineer
  • AI / GenAI Engineer
  • MLOps / AI Platform Engineer
  • AI Application Engineer
What You'll Do

Depending on the role, you will:

  • Design, train and deploy ML and GenAI models for real-world applications
  • Build LLM-based applications, RAG pipelines and AI-powered APIs
  • Develop scalable MLOps pipelines for model training, validation, CI/CD and monitoring
  • Work with cloud platforms (AWS, Azure, GCP) and GPU/accelerated workloads
  • Integrate AI models into web and backend applications
  • Monitor model performance, drift and reliability in production
What We're Looking For (Mid-Level)
  • 3–7 years of experience in ML / AI / MLOps / AI Engineering
  • Strong programming in Python (PyTorch, TensorFlow, scikit-learn)
  • Experience with LLMs, prompt engineering, vector databases and RAG frameworks
  • Knowledge of Docker, Kubernetes, CI/CD and cloud ML services
  • Experience with APIs, microservices and production deployments
Preferred Skills & Certifications
  • Experience with OpenAI, Azure OpenAI, Vertex AI, Bedrock, Hugging Face
  • MLOps tools: MLflow, Kubeflow, Airflow, Weights & Biases
  • Cloud certifications or AI/ML certifications
  • Exposure to data pipelines, streaming and feature stores

Cogent Infotech is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment where everyone feels welcome and valued. We encourage applications from individuals of all backgrounds, identities, abilities, and experiences. If you're excited about this role but don't meet every requirement, we still encourage you to apply.

At Cogent Infotech, your ideas matter. Join a purpose-driven organization that celebrates diversity, encourages collaboration, and invests in your future.