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Remote Aws Machine Learning Jobs in Boston, MA (NOW HIRING)

Remote AI Architect

Boston, MA · Remote

$90 - $92/hr

Remote AI Architect needs 10+ years' experience enterprise-wide AI programs or platform buildouts ... Strong hands-on experience with machine learning frameworks and LLM platforms (e.g., OpenAI, Azure ...

Senior Applied Data Scientist

Boston, MA · On-site +1

$150K - $180K/yr

... machine learning systems in a cloud-based platform, such as AWS SageMaker * Experience developing ... Remote -- United States Employment type: Full-time About 3Play Media 3Play Media is a technology ...

... machine learning solutions on platforms such as AWS, Databricks, Azure, Google Cloud and OpenAI ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Senior Solutions Architect

Boston, MA · Remote

$130K - $160K/yr

Remote - United States Job Type: Full-Time, Permanent About Exemplar Companies Exemplar Companies ... machine learning, and large language models (LLMs) technologies. * Familiarity with AWS Bedrock ...

Design, build and implement machine learning models, including the development of AI Models and ... AWS. * Experience building and optimizing API's and data pipelines, architectures and data sets.

Principal Software Engineer- AI

Boston, MA · On-site +1

$174K - $287K/yr

Deep understanding of machine learning frameworks and experience in Generative AI application ... Experience developing highly scalable backend microservices in AWS Personal qualities and ...

Showing results 41-60

Remote Aws Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote AWS Machine Learning Engineer, and why are they important?

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What are remote AWS Machine Learning jobs?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

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

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.
What are the most commonly searched types of Aws Machine Learning jobs in Boston, MA? The most popular types of Aws Machine Learning jobs in Boston, MA are:
What are popular job titles related to Remote Aws Machine Learning jobs in Boston, MA? For Remote Aws Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in Boston, MA look for? The top searched job categories for Remote Aws Machine Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Remote Aws Machine Learning jobs? Cities near Boston, MA with the most Remote Aws Machine Learning job openings:
Senior Director, AI Engineering -Agentic AI Platform(Remote Eligible)

Senior Director, AI Engineering -Agentic AI Platform(Remote Eligible)

Capital One

Cambridge, MA • On-site, Remote

$276K/yr

Full-time

Posted 4 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 145 frontline employees who took The Breakroom Quiz

91st of 170 rated banks


Job description

Senior Director, AI Engineering -Agentic AI Platform(Remote Eligible)

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

  • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One

  • Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

  • Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more

  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems

  • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

  • Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI

Capital One is open to hiring a Remote Employee for this opportunity

The Ideal Candidate:

  • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good

  • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production

  • You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example

  • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven

  • You are deeply technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss

  • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown

Basic Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing or leading AI and ML algorithms or technologies

  • At least 5 years of people leadership experience

Preferred Qualifications:

  • 7 years of experience managing and leading an engineering team

  • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory)

  • Master's degree in Computer Science, Computer Engineering, or relevant technical field

  • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Remote (Regardless of Location): $286,200 - $326,700 for Sr. Director, AI Engineering


Cambridge, MA: $314,800 - $359,300 for Sr. Director, AI Engineering


McLean, VA: $314,800 - $359,300 for Sr. Director, AI Engineering


New York, NY: $343,400 - $392,000 for Sr. Director, AI Engineering


San Francisco, CA: $343,400 - $392,000 for Sr. Director, AI Engineering


San Jose, CA: $343,400 - $392,000 for Sr. Director, AI Engineering






Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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