1

Junior Aws Machine Learning Jobs in Wisconsin (NOW HIRING)

WI · On-site

$206.26 - $330.02/hr

We use PySpark for most of our data processing, AWS SageMaker Studio for model development and validation, and PyTorch + HuggingFace for deep learning work. Model inference runs on a mix of FastAPI ...

AI Engineer II

Middleton, WI · On-site

$100K - $137K/yr

Write, test, and ship real AI and machine learning code that makes it into production, with support ... Comfortable building on cloud platforms such as Microsoft Azure, AWS, or Google Cloud * Experience ...

AI Engineer II

Middleton, WI · On-site

$100K - $137K/yr

Write, test, and ship real AI and machine learning code that makes it into production, with support ... Comfortable building on cloud platforms such as Microsoft Azure, AWS, or Google Cloud * Experience ...

AI Engineer II

Middleton, WI · On-site

$100K - $137K/yr

Write, test, and ship real AI and machine learning code that makes it into production, with support ... Comfortable building on cloud platforms such as Microsoft Azure, AWS, or Google Cloud * Experience ...

WI · On-site

$120 - $150/hr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning ... Experience with APIs, CI/CD pipelines, cloud platforms (AWS/Azure/GCP). * Ability to clearly ...

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

WI · On-site

Staff Software Engineer - AI/ML Staff Machine Learning Engineer, CustomerLake (ML/LLM) RDQ427R109: At the company, we are passionate about enabling data teams to solve the world's toughest problems ...

WI · On-site

$130 - $160/hr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... Provide technical guidance and mentorship to junior data scientists and engineers. * Work directly ...

Showing results 41-60

Junior Aws Machine Learning information

What is a junior AWS machine learning engineer?

Junior AWS Machine Learning engineers are entry-level professionals who work with Amazon Web Services (AWS) to develop, deploy, and maintain machine learning models. They assist in data preparation, model training, and integration of AI solutions using AWS tools such as SageMaker, Lambda, and S3. These engineers often collaborate with data scientists and software teams to implement predictive analytics and automation solutions on the AWS cloud platform. Their role typically involves learning best practices for cloud security, data handling, and scalable machine learning deployment.

What are the key skills and qualifications needed to thrive as a junior AWS machine learning engineer?

To thrive as a Junior AWS Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with AWS services like SageMaker, Lambda, and S3, as well as certifications such as AWS Certified Machine Learning – Specialty, are highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical ideas clearly help you stand out in this role. These skills and qualities are crucial for efficiently developing, deploying, and maintaining machine learning solutions on AWS in collaborative, fast-paced environments.

Are there entry level AWS jobs?

Yes, there are entry-level AWS jobs such as Junior AWS Machine Learning roles that typically require foundational knowledge of cloud computing, basic understanding of machine learning concepts, and familiarity with AWS services like S3, EC2, and SageMaker. These roles often serve as starting points for careers in cloud and machine learning fields and may require certifications like AWS Certified Cloud Practitioner or AWS Certified Machine Learning – Specialty. Candidates should be prepared to learn on the job and develop skills through training and hands-on experience.

What are some common challenges faced by junior AWS machine learning engineers when deploying models to production environments?

Junior AWS Machine Learning Engineers often encounter challenges such as managing the scalability of their models, ensuring data security and compliance in the cloud, and integrating machine learning pipelines with existing AWS services. Since production environments require high reliability, newcomers may also need to learn how to monitor model performance and troubleshoot issues using AWS tools like SageMaker and CloudWatch. Collaborating closely with data engineers and DevOps teams is essential to streamline deployment and maintain model accuracy over time.

What is the difference between Junior Aws Machine Learning vs Data Scientist?

AspectJunior Aws Machine LearningData Scientist
Required CredentialsBasic AWS certifications, entry-level ML knowledgeAdvanced degrees, certifications like AWS, data analysis skills
Work EnvironmentCloud platforms, machine learning projects, collaborative teamsData analysis, modeling, research, cross-functional teams
Employer & Industry UsageTech companies, startups, cloud service providersFinance, healthcare, tech, research institutions

Junior AWS Machine Learning roles focus on implementing ML models using AWS tools with foundational knowledge, while Data Scientists typically handle broader data analysis, modeling, and research tasks. The roles overlap in cloud-based ML work but differ in scope and experience level.

What are the most commonly searched types of Aws Machine Learning jobs in Wisconsin? The most popular types of Aws Machine Learning jobs in Wisconsin are:
What are popular job titles related to Junior Aws Machine Learning jobs in Wisconsin? For Junior Aws Machine Learning jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Junior Aws Machine Learning jobs in Wisconsin look for? The top searched job categories for Junior Aws Machine Learning jobs in Wisconsin are:
What cities in Wisconsin are hiring for Junior Aws Machine Learning jobs? Cities in Wisconsin with the most Junior Aws Machine Learning job openings:

Staff Machine Learning Engineer (Open to Remote)

TBK Bank, SSB

WI • On-site

$206.26 - $330.02/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


Job description

Join Triumph! At Triumph, our vision is a world where freight transactions are accurate and seamless on the most modern and secure freight transaction network. That’s why we’re looking for passionate, innovative, solutions-oriented people to join our team. We thrive on providing exceptional customer service and we look for team members with an entrepreneurial spirit and a passion to build successful partnerships with our clients. Because at the end of the day our goal is to help our partners businesses run better.

Join Triumph! At Triumph, our vision is a world where freight transactions are accurate and seamless on the most modern and secure freight transaction network. That’s why we’re looking for passionate, innovative, solutions-oriented people to join our team. We thrive on providing exceptional customer service and we look for team members with an entrepreneurial spirit and a passion to build successful partnerships with our clients. Because at the end of the day our goal is to help our partners businesses run better.

Join Triumph! At Triumph, our vision is a world where freight transactions are accurate and seamless on the most modern and secure freight transaction network. That’s why we’re looking for passionate, innovative, solutions-oriented people to join our team. We thrive on providing exceptional customer service and we look for team members with an entrepreneurial spirit and a passion to build successful partnerships with our clients. Because at the end of the day our goal is to help our partners businesses run better.

At TriumphPay we are building the transportation payments network for the future. Our software touches a combined $37.1B in annualized freight volume, representing over 20% of the brokered freight market in the U.S. TriumphPay’s customers are using our products to solve real world problems. This is both exciting and also an incredible responsibility. We are looking for experienced Staff ML engineers to join our team of 35+ engineers. If you join TriumphPay, you will work closely in a small, cross-functional team of 3-4 people focused on our AI/ML systems. Our teams operate with a high degree of autonomy, allowing you to take ownership of projects from ideation to deployment. You’ll collaborate closely with product managers and other stakeholders to understand customer pain points and deliver impactful solutions that support critical features. Our engineering team is fully remote and believes strongly in work-life balance.

A Day In The Life:

There’s no defined template that teams at TriumphPay follow, allowing each team to build the day that lets them perform at their best. Typically, a team has a morning standup allowing them to catchup on what happened yesterday, and ensure there’s a plan in place for the day ahead. You’ll work with our product group and members of the sales team to ensure we’re building the tools our customers need to succeed.

The Tech:

The AI/ML team works primarily in a mixture of Python and Clojure for ML experimentation, data processing, and deployments, with Ruby and other languages used for integrating models into customer-facing applications. Python and Ruby make up the majority of our work, with Clojure being third. Occasionally, the AI/ML team handles integration work in Ruby or other languages directly when it enables faster delivery of value, though this work may also be handed off to feature development teams. We use PySpark for most of our data processing, AWS SageMaker Studio for model development and validation, and PyTorch + HuggingFace for deep learning work. Model inference runs on a mix of FastAPI and Clojure applications, depending on the model type. Our ML systems process more than 1 million documents per day through hundreds of models requiring robust pipelines to handle noisy, unstructured data with high precision at scale. You'll work on building, deploying, and integrating models that can generalize across diverse document formats and adapt to evolving customer needs. Our models must operate within strict latency requirements to ensure seamless customer experiences, while maintaining high performance in extracting and classifying data from complex, unstructured documents. We are constantly exploring new techniques in deep learning, transfer learning, and model optimization to improve the accuracy and efficiency of our systems. We know that good engineers can pick up new tools and languages on the job and we don't expect candidates to be familiar with all of these technologies. We love curious individuals who believe they can always improve, and we know that good developers are capable of picking up new languages and tools. Engineers are provided a top of the line MacBook to do their work, and you’ll have access to all the necessary tooling to do the non-coding parts of your job (Zoom, Slack, etc.).

To succeed in this role, you should be:
  • Curious. You aren't content with the status quo and know that we can always improve.
  • Data Driven. You seek evidence to support hypotheses and identify optimal solutions within problem constraints accounting for sources of error and uncertainty.
  • Collaborative. You can work with others to improve a solution iteratively factoring in new information from outside perspectives.
  • Empathetic. Your designs are influenced by a deep understanding of the customers' needs.
  • A strong communicator. You will proactively communicate issues and trade-offs with team members to support alignment and fast decision making.
  • Be an outstanding developer. Your peers should recognize you as one of the best and the brightest developers they have worked with.
We hope you bring into this role:
  • 10+ years of software engineering experience;
  • 4+ years with production ML at scale.
  • Proven success designing and operating distributed ML systems.
  • Strong experience with model deployment patterns and data pipelines.
  • Demonstrated ability to influence technical decisions across teams.
  • Deep understanding of reliability engineering and production support.
Success at Triumph Looks Like:
  • Leading multi-team ML initiatives that deliver sustained business value.
  • Establishing clear, repeatable ML engineering standards adopted across teams.
  • Reducing friction from experimentation to production.
#LI-JC1 Compensation Range Annual Salary:

$206,261.00 - $330,017.00

Location:

Dallas, TX or Remote U.S. excluding the following states: AK, DE, RI, VT, WY

We offer
  • Medical, Dental, Vision, Paid Time Off, 401k and much more.
OUR BUSINESS

Triumph is a financial and technology company focused on payments, factoring, intelligence and banking. We are pioneering solutions that serve the transportation industry. Through the Triumph brand, our customers gain unrivaled efficiency, transparent and secure transactions, and improved access to working capital. Through TBK Bank, we provide personal and business banking solutions that strengthen local communities and fortify our transportation business. We create value by driving businesses and communities of all sizes toward the future.

We are proud to be an equal opportunity employer and we do not discriminate in recruitment, hiring, training, promotion, or other employment practices on the basis of age, race, gender, color, religion, national origin, disability, sexual orientation, veteran status, or any other basis that is prohibited by federal, state or local law.

As a member of the Triumph team, you’re at the heart of an innovative, forward-thinking company that values collaboration, creativity and continuous learning. You’re not just an employee — you’re part of a team shaping the future. Being part of Triumph means striving for excellence while delivering with humility.

OUR CORE VALUES

Our long-standing core values are based on sound business practices and biblical principles. They flourish in our culture which helps our team members thrive, our customers succeed and our communities prosper. We commit ourselves to:

  • Transparency
  • Respect
  • Invest for the future
  • Unique is good
  • Mission is more than money
  • People make the difference
  • Humility
FOCUS ON SERVING OTHERS

At Triumph, we strive to do the most good in the areas of greatest needs through our philanthropic endeavors. Our philanthropic vision is centered on four areas:

  • Advocating for safety and justice
  • Providing access to basic needs
  • Supporting families
  • Transforming communities
#J-18808-Ljbffr