Machine Learning (ML) Consultant, AWS Professional Services

Amazon; Asti; In loco; EUR 50.000 - 75.000; Tempo pieno

Descrizione del lavoro

A global cloud services provider is seeking a Machine Learning Consultant to design and implement advanced ML models. In this role, you'll collaborate with engineers and customers, driving innovative solutions to real-world challenges. Ideal candidates have a strong background in ML, experience with deep learning frameworks, and a BSc degree in a relevant field. Join a diverse team committed to advancing cloud-based technologies with a focus on mentorship and work-life balance.

Servizi

Mentorship opportunities

Career growth resources

Work-life balance initiatives

Competenze

• 4+ years of experience in building machine learning models for business applications.
• Scientific thinking and experience in planning, designing, implementing, and evaluating experiments.
• Experience in conveying rigorous technical concepts to both technical and non-technical audiences.

Mansioni

• Collaborate with engineers to design, develop, and evaluate ML algorithms.
• Lead customer interactions to define and implement ML solutions.
• Create and deliver best practice recommendations and tutorials.

Conoscenze

Machine Learning

Neural Deep Learning

Data Quality Management

Customer Facing Skills

Formazione

BSc degree in Computer Science, Physics, Mathematics, Engineering or related

Strumenti

PyTorch

TensorFlow

Huggingface

Descrizione del lavoro

Machine Learning (ML) Consultant, AWS Professional Services

Job ID: 3086924 | Amazon Web Services Australia Pty Ltd

AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.

As a Machine Learning (ML) Consultant, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for ML Consultant capable of using ML, GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Key job responsibilities

• Collaborate with engineers to research, design, develop, and evaluate state-of-the-art ML and generative AI algorithms to address real-world challenges across industries
• Lead customer interactions to deeply understand the business problem, and help them in defining and implementing ML and generative AI solutions, as well as guide them on adoption patterns and paths to production
• Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and develop new solutions
• Create and deliver best practice recommendations, scientific artifacts, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders
• Effectively communicate complex ML results and insights to diverse audiences, translating technical concepts for non-technical stakeholders while providing appropriate depth for technical audiences in both public-facing publications and internal knowledge sharing sessions

A day in the life
AWS Professional Services (ProServe) is a global team of consultants that helps enterprise customers achieve their business outcomes on AWS Cloud. ProServe consultants work with hundreds of the world’s largest enterprises to help them deliver their cloud initiatives.

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, 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
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

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.

Basic Qualifications

• BSc degree in Computer Science, Physics, Mathematics, Engineering or related, with 4+ years of experience in building machine learning models for business applications
• Scientific thinking and experience to plan, design, implement and evaluate experiments, with rigorous analysis capabilities.
• Experience with neural deep learning methods and machine learning
• Hands on experience building models with deep learning frameworks like PyTorch, Tensorflow, or Huggingface
• Experience in conveying rigorous technical concepts and considerations to technical and non-technical audiences

Preferred Qualifications

• Ability to think strategically about business, product, and technical challenges in an enterprise environment
• Hands on experience leading large-scale global data analytics projects aligned with business use cases.
• Experience in Data Quality management: Processes to measure and manage data quality, enforce data controls, and provide data assurance.
• Implementing AWS services in a variety of distributed computing, enterprise environments
• Customer facing skills to represent AWS well within the customer’s environment and drive discussions with senior personnel regarding trade-offs, best practices, project management and risk mitigation

Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.

IDE statement:
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.