Search for senior machine learning engineer roles in Arlington, VA, focusing on AWS technologies, requiring 5+ years of experience, with a preference for remote job options.

Okay, I've searched for senior machine learning engineer roles in Arlington, VA, focused on AWS technologies, requiring 5+ years of experience, with options for remote work. I found 87 positions that match your criteria.

Senior Machine Learning Engineer

Arlington, VA

5 years + Experience

Remote

AWS

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The Senior Delivery Consultant - Senior Machine Learning Engineer role at AWS is fundamentally about leveraging substantial expertise in machine learning and artificial intelligence to drive customer adoption of advanced cloud solutions. This position requires not just technical acumen but also strategic thinking to guide global enterprises through complex data challenges and the integration of generative AI capabilities. Responsibilities include leading project teams from inception to delivery, designing and implementing robust ML systems, and ensuring the solutions are scalable, secure, and aligned with the customer's business objectives. Candidates will face challenges such as aligning diverse stakeholder needs, managing project risks, and navigating the often rapidly evolving landscape of AI technology. Success in this role will be judged by customer satisfaction, the effectiveness of the deployed solutions, and the ability to innovate within the AWS ecosystem, all while fostering knowledge sharing and best practices within the team.

Company Analysis:

Amazon Web Services (AWS) is a leading cloud service provider renowned for its expansive and robust cloud solutions. AWS positions itself as an innovator in the industry, continuously pushing the boundaries of cloud technology and AI solutions. This creates a dynamic and fast-paced environment that emphasizes agility, innovation, and customer-centric approaches. The company's culture is likely to reflect values of inclusivity, curiosity, and mentorship, fostering a collaborative workplace where diverse experiences are valued. As a Senior Machine Learning Engineer, you'll be embedded within a global team, meaning your contributions will significantly impact AWS's operational success and innovation trajectory. Moreover, the increasing reliance on AI and machine learning in businesses present greater urgency and importance for this role, underscoring how the position aligns with the company's strategic emphasis on advanced technology solutions for enterprise clients.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Describe a time when you led a technical team through a challenging project. What approach did you take, and what was the outcome?
Can you provide an example of a machine learning model you developed and deployed? What were the key challenges you faced?
How do you prioritize competing projects or requirements when working on a delivery? Can you discuss a specific instance?
Tell me about a situation where you had to explain a complex technical concept to a non-technical audience. How did you ensure they understood?
What strategies would you use to assess the current infrastructure of a customer before implementing an AI/ML solution?
Describe your experience with cloud platforms, specifically AWS services. Which services have you used, and in what context?
How do you approach designing scalable and secure machine learning solutions? Can you walk through your process?
Imagine a client is hesitant about adopting a new AI technology after a previous setback. How would you address their concerns and guide them through the adoption process?
You are tasked with optimizing the performance of a deployed machine learning model. What steps would you take to diagnose and improve its efficiency?
What interests you most about working for Amazon Web Services, and how do you see yourself contributing to our mission?
How do your professional values align with AWS's commitment to innovation and inclusion?
What do you think is the future of AI and machine learning in cloud computing, and how does that vision align with AWS's goals?
What questions do you have about our projects or technologies that you would be working on in this role?
Can you describe any experiences you have with MLOps practices and how they informed your machine learning deployments?
How do you stay updated on industry trends and emerging technologies in AI/ML?

Job Details

Overview Company

Senior Machine Learning Engineer

$138.2k/y-$239k/y

Amazon Web Services (AWS)

12 days ago

Highlight

OnsiteFull-time8+ yearsSenior

Summary

Amazon Web Services (AWS) is seeking a Senior Delivery Consultant - Senior Machine Learning Engineer to join their AWS Professional Services team in Arlington, VA. The role involves designing, implementing, and managing AWS AI/ML and GenAI solutions to meet customer technical requirements and business objectives.

About the Role

As a Senior Delivery Consultant, you will lead project teams and implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment, and monitoring. You will design scalable ML solutions and operations using AWS services, collaborate with cross-functional teams, and serve as a trusted advisor to customers on AI/ML and GenAI solutions. The role includes mentoring, training, and ensuring solutions meet industry standards.

About You

Required:

5+ years cloud architecture and implementation experience.
Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience.
8+ years leading technical teams and hands-on experience focused on data, software, or ML engineering.
5+ years developing predictive modeling, natural language processing, and deep learning.
5+ years developing with SQL, Python, and at least one additional programming language.
Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch).

Preferred:

AWS experience with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2).
AWS Professional certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional).
Experience with automation, Infrastructure as Code, and Containers & CI/CD Pipelines.
Knowledge of common security and compliance standards (e.g., HIPAA, GDPR).
Strong communication skills with the ability to explain complex concepts to technical and non-technical audiences.
Experience building ML pipelines with MLOps best practices.
Experience with MLOps and orchestration tools.
Experience building applications using GenAI technologies.

Benefits

Compensation ranges from $138k–$239k based on market location and experience.
Equity, sign-on payments, and other forms of compensation may be provided.
Full range of medical, financial, and other benefits.

Amazon Web Services (AWS)

Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. The ultimate benefit of cloud computing, and AWS, is the ability to leverage a new business model and turn capital infrastructure expenses into variable costs. Businesses no longer need to plan and procure servers and other IT resources weeks or months in advance. Using AWS, businesses can take advantage of Amazon's expertise and economies of scale to access resources when their business needs them, delivering results faster and at a lower cost.

Today, Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. With data center locations in the U.S., Europe, Singapore, and Japan, customers across all industries are taking advantage of our low cost, elastic, open and flexible, secure platform.

Arlington, VA