Delivery Consultant - AI/ML, ML Engineer

Amazon is hiring a Delivery Consultant - AI/ML, ML Engineer in Warsaw, Poland. Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
Tools and skills the posting cites include LangChain, PyTorch and TensorFlow.
Level classifies it as a senior role.
Level lists 21,000+ other open roles at Amazon.
The role was posted within the past week.

AI in this role

Design and build complex GenAI and machine learning applications and models on AWS for enterprise customers.

langchainpytorchtensorflowscikit-learnaws

fine-tuningmachine-learninggenerative-aicloud-computingmodel-deployment

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle.

Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.

Key job responsibilities
Key job responsibilities
As an experienced technology professional, you will be responsible for:
- Designing, implementing, and building complex, scalable, and secure GenAI and ML applications and models built on AWS tailored to customer needs
- Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services
- Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies
- Acting as a trusted advisor to customers on industry trends and emerging technologies
- Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts

About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic qualifications

- 2+ years of experience hosting and deploying GenAI/ML solutions (e.g., for training, fine tuning, and inferences)
- 4+ years of experience in technical architecture, design, deployment and operations for AI platforms, standards, protocols and devices.
- 4+ years of experience in predictive modelling and analysis, predictive software development.
- 3+ years professional experience in software development in languages related to ML such as Python,TypeScript and/or R.
- Experience using machine learning libraries, such as scikit-learn, Apache MxNet, PyTorch, and TensorFlow, Langchain, Strands, MCP
- English language proficiency is a must.

Preferred qualifications

- An MS/PhD in Computer Science, Machine Learning, Operational research, Statistics or in a highly quantitative field.
- A strong data scientist with a background and experience in software engineering with software development / script development (Python, R, TypeScript, React, C/C++, or similar).
- Experience in AWS Platforms and Services
- AWS Associate, Speciality or Professional Certification
- Experience with Agile execution
- Track record of presenting at public events such as technology conferences, hackathons or blogging, writing technical articles or contributing to open source projects.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The minimum gross base salary for this position is listed below. The base salary listed corresponds to working on a full-time basis. For part-time hours, the salary will be pro-rated.

Amazon reserves the right to offer a higher base salary, depending on the candidate's skills, competencies, and experience. Amazon's package may include a sign on payment. In addition, the candidate may be eligible to participate in a restricted stock unit scheme operated independently by Amazon.com Inc. in USA. Your recruiting team will share final salary and any restricted stock unit scheme if applicable, depending on skills and requirements.

Company supplementary benefits apply subject to further terms, including pension plans, health insurance, life and disability insurance, business travel insurance, MultiSport card, employee discount code and program (EDC/Extras), and the Employee Assistance Program (private and confidential counselling and referral service to support health and well-being).

See below the minimum gross base salary for this position:

Warsaw, POL - 18,141.67 PLN Monthly

How we rate this

Delivery Consultant - AI/ML, ML Engineer at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Delivery Consultant - AI/ML, ML Engineer is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in PL, Warsaw.
The job was posted on October 19, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningMachine learningGenerative AICloud ComputingModel DeploymentLangChainPyTorchTensorFlow

Also common in machine learning engineer jobs at this level

LLM Deep learning Kubernetes Spark MLOps Google Cloud

Pay

Typical machine learning engineer job: $199k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where generative ai was part of your work. What did you do?
Tell me about a project where cloud computing was part of your work. What did you do?
Tell me about a project where model deployment was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Fine-tuning, Machine learning, Generative AI, Cloud Computing, and Model Deployment. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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