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Amazon Machine Learning Jobs in Dallas, TX (NOW HIRING)

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years ... Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in ... Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a ...

Resolve Tech Solutions

AI & ML Intern

Addison, TX

Artificial Intelligence & Machine Learning (AI & ML) Intern Position Title: AI & ML Intern ... Experience with LangChain, Crew AI, Amazon Bedrock, Google Vertex AI or Azure OpenAI Cognitive ...

Resolve Tech Solutions

AI & ML Intern

Addison, TX · On-site

Artificial Intelligence & Machine Learning (AI & ML) Intern Position Title: AI & ML Intern ... Experience with LangChain, Crew AI, Amazon Bedrock, Google Vertex AI or Azure OpenAI Cognitive ...

Deloitte

Manager - Data Science / Data Lake

Dallas, TX · On-site

... or support machine learning workflows • Experience working with cyber security cloud platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure, and exposure to security ...

New

Deloitte

AI Solutions Leader

Dallas, TX · On-site

Experience with at least one cloud platform, such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform, and artificial intelligence and machine learning tools and frameworks * Ability to ...

Amazon

Sr. Cloud Solutions Consultant, FedFin

Dallas, TX · On-site

$57.75 - $79/hr

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery ... machine learning, and serverless technologies - Experience in performance optimization and cost ...

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Amazon Machine Learning information

See Dallas, TX salary details

$25.3K

$42.3K

$87.4K

How much do amazon machine learning jobs pay per year?

As of May 29, 2026, the average yearly pay for amazon machine learning in Dallas, TX is $42,304.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 per year, depending on experience, location, and employer.

What is an Amazon Machine Learning job?

An Amazon Machine Learning job involves developing, deploying, and optimizing machine learning models to improve products and services within Amazon. Professionals in this role work with large-scale data, build predictive models, and collaborate with engineering and business teams to drive data-driven decisions. Responsibilities may include data preprocessing, feature engineering, model training, and deploying machine learning solutions in production. Strong programming skills, proficiency in ML frameworks, and experience with AWS services like SageMaker are often required.

What are the key skills and qualifications needed to thrive in the Amazon Machine Learning position, and why are they important?

To excel in an Amazon Machine Learning role, you should possess strong expertise in machine learning algorithms, statistical analysis, programming (Python, Java, or Scala), and typically hold a degree in computer science, engineering, or a related field. Familiarity with AWS cloud services (like SageMaker, EC2, S3), big data frameworks, and relevant certifications such as AWS Certified Machine Learning are highly valuable. Effective communication, problem-solving skills, and the ability to work collaboratively in diverse teams help distinguish top candidates. These skills are crucial for developing scalable AI solutions, translating business problems into technical models, and successfully integrating them into Amazon’s large-scale operations.

What types of projects and daily tasks can I expect in an Amazon Machine Learning position?

As an Amazon Machine Learning professional, your daily work may involve designing and deploying machine learning models, analyzing large datasets, and collaborating with cross-functional teams such as data engineers and product managers. You’ll frequently participate in code reviews, troubleshoot complex algorithms, and help optimize model performance for various Amazon products and services. Projects often range from natural language processing and recommendation systems to forecasting and computer vision initiatives. This dynamic environment offers exposure to cutting-edge innovation and opportunities to grow your technical and leadership skills within a global technology leader.
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What are popular job titles related to Amazon Machine Learning jobs in Dallas, TX? For Amazon Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:
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What cities near Dallas, TX are hiring for Amazon Machine Learning jobs? Cities near Dallas, TX with the most Amazon Machine Learning job openings:
Amazon Machine Learning jobs near you
Infographic showing various Amazon Machine Learning job openings in Dallas, TX as of May 2026, with employment types broken down into 100% Full Time. Highlights an 58% In-person, 18% Hybrid, and 24% Remote job distribution, with an average salary of $42,304 per year, or $20.3 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Ascentt

Plano, TX • On-site

$100K - $137.30K/yr

Full-time

Posted 22 days ago

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring passionate builders to shape the future of industrial intelligence.
Job Title: Senior Machine Learning Engineer
Location: Ann Arbor, Michigan
Experience Level: 7+ Years
Department: Data Science / Engineering
Employment Type: Full-time
About the Role:
We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud environments. The ideal candidate will be a self-starter with strong problem-solving skills and hands-on experience in building and deploying ML models using big data technologies like PySpark and cloud platforms like Amazon SageMaker.
Key Responsibilities:
  • Design, develop, and deploy scalable machine learning models for real-world business problems using structured and unstructured data.
  • Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines.
  • Apply a wide range of statistical, machine learning, and deep learning techniques, including but not limited to regression, classification, clustering, time-series forecasting, and NLP.
  • Own end-to-end ML pipelines from data ingestion, preprocessing, training, validation, tuning, and deployment.
  • Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a production-grade environment.
  • Collaborate closely with data engineers, data scientists, and product teams to integrate models with business workflows.
  • Monitor and improve model performance, scalability, and reliability in production.
  • Contribute to setting up and maintaining the ML environment and tooling (including environment configuration, CI/CD pipelines for ML, model versioning, etc.).

Required Qualifications:
  • 7+ years of experience in machine learning, data science, or related fields.
  • Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
  • Hands-on experience with PySpark for big data processing and model development.
  • Proficient in building models on large-scale datasets (terabytes to petabytes).
  • Solid understanding of statistical analysis, probability, hypothesis testing, and experimental design.
  • Experience with Amazon SageMaker (or similar cloud-based ML platforms).
  • Strong knowledge of ML Ops practices including version control, model monitoring, and retraining strategies.
  • Familiarity with containerization (Docker) and CI/CD practices for ML projects is a plus.
  • Excellent communication skills and the ability to clearly explain complex concepts to non-technical stakeholders.

Preferred Qualifications:
  • Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
  • Experience with workflow orchestration tools (e.g., Airflow, Kubeflow).
  • Prior experience in domains like Manufacturing, finance, healthcare, or e-commerce is a plus.

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