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Remote Aws Machine Learning Jobs in Philadelphia, PA

Define and drive SEI's AI strategy across Machine Learning, Generative AI, Agentic AI, and ... Strong cloud expertise in Azure, AWS, or GCP, including AI platform services and production ...

Senior Software Engineer (Remote)

Philadelphia, PA · Remote

$123K - $163K/yr

Familiarity with LLMs, AI agents, embeddings, or other machine-learning capabilities and their ... AWS, and Terraform. * Experience with PostgreSQL, MySQL, Redis, or similar databases and data ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

A specialization in machine-learning, artificial intelligence, cognitive science or data science is ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

A specialization in machine-learning, artificial intelligence, cognitive science or data science is ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Showing results 41-60

Remote Aws Machine Learning information

What is a remote AWS Machine Learning job?

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 are the key skills and qualifications needed to thrive as a remote AWS Machine Learning engineer?

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 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 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 popular job titles related to Remote Aws Machine Learning jobs in Philadelphia, PA?

For Remote Aws Machine Learning jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Remote Aws Machine Learning jobs in Philadelphia, PA look for?

The top searched job categories for Remote Aws Machine Learning jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Remote Aws Machine Learning jobs?

Cities near Philadelphia, PA with the most Remote Aws Machine Learning job openings:

Lead Data Scientist

SEI Investments

Oaks, PA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago


SEI Investments rating

8.8

Company rating: 8.8 out of 10

Based on 11 frontline employees who took The Breakroom Quiz


Job description

SEI is seeking an accomplished and visionary Lead Data Scientist, Generative AI & Intelligent Systems to lead the next generation of AI innovation across the enterprise. This leader will define and execute SEI's AI strategy spanning traditional machine learning, Generative AI, Agentic AI, intelligent automation, and AI-powered digital experiences. The role will drive the design, development, and deployment of scalable AI solutions including enterprise copilots, RAG-based knowledge systems, AI agents, intelligent workflow automation, and advanced predictive analytics.

Working closely with business leaders, product teams, architects, cybersecurity, and engineering teams, this individual will transform emerging AI capabilities into practical business solutions while establishing scalable frameworks, governance standards, and AI best practices across the organization.

What You Will Do

  • Define and drive SEI's AI strategy across Machine Learning, Generative AI, Agentic AI, and Intelligent Automation initiatives.
  • Lead the design and delivery of enterprise-scale AI solutions including:
    • Generative AI applications
    • RAG (Retrieval-Augmented Generation) platforms
    • Conversational AI and enterprise chatbots
    • AI copilots and virtual assistants
    • Multi-agent and agentic AI systems
    • Knowledge discovery and search solutions
  • Architect AI systems that integrate Large Language Models (LLMs), enterprise knowledge repositories, APIs, and business workflows while ensuring scalability, security, and governance.
  • Evaluate emerging AI technologies, foundation models, frameworks, orchestration platforms, and agentic architectures to determine strategic fit for SEI.
  • Lead AI product development from ideation through deployment, including experimentation, prototyping, productionization, monitoring, and continuous improvement.
  • Establish best practices and standards for LLMOps, AI governance, prompt engineering, model evaluation, AI safety, observability, and responsible AI.
  • Partner with business stakeholders to identify high-value AI opportunities and translate business challenges into innovative AI-powered solutions.
  • Design and oversee RAG pipelines, vector databases, semantic search architectures, and knowledge management solutions.
  • Guide the development of AI-enabled products leveraging structured and unstructured data sources.
  • Collaborate with security, privacy, legal, and risk teams to ensure AI solutions meet regulatory, governance, and compliance requirements.
  • Mentor and develop data scientists, AI engineers, architects, and technical leaders while fostering a culture of innovation, experimentation, and continuous learning.
  • Communicate AI strategy, solution architectures, business value, and technical insights to executive leadership and non-technical stakeholders.

What We Need From You

  • Bachelor's degree from an accredited college or university and/or equivalent relevant experience. MS, MBA, PhD, or CFA designation is a plus.
  • 10+ years of experience in Artificial Intelligence, Data Science, Machine Learning, Software Engineering, or related disciplines.
  • Demonstrated experience delivering enterprise-scale Generative AI and Machine Learning solutions from concept through production.
  • Deep expertise in Large Language Models (LLMs), Generative AI architectures, Retrieval-Augmented Generation (RAG), prompt engineering, and AI orchestration frameworks.
  • Strong experience designing AI applications using technologies such as Azure AI, OpenAI, Anthropic, LangChain, Semantic Kernel, AutoGen, CrewAI, MCP, vector databases, and related AI ecosystems.
  • Strong understanding of Agentic AI patterns including planning, orchestration, memory, tool use, workflow automation, and multi-agent systems.
  • Experience implementing AI governance, model evaluation, AI observability, security controls, and responsible AI frameworks.
  • Strong cloud expertise in Azure, AWS, or GCP, including AI platform services and production deployment architectures.
  • Advanced Python development skills and experience building scalable AI applications and APIs.
  • Experience working with structured and unstructured data, knowledge repositories, search platforms, and document intelligence solutions.
  • Proven ability to balance innovation with governance, risk management, security, and operational excellence.

What We Would Like From You

  • Demonstrated thought leadership in Artificial Intelligence, Generative AI, Agentic AI, or related emerging technologies.
  • Experience defining enterprise AI roadmaps, operating models, governance structures, and adoption strategies.
  • Strong understanding of financial services, wealth management, or regulated industry environments.
  • Exceptional communication and executive presentation skills with the ability to influence senior leadership and stakeholders.
  • Proven ability to lead cross-functional teams consisting of AI engineers, data scientists, architects, product managers, cybersecurity professionals, and business leaders.
  • Experience evaluating third-party AI platforms, vendors, and strategic partnerships.
  • Strong product mindset with an ability to translate complex business challenges into scalable AI products and capabilities.
  • Excellent analytical, problem-solving, and strategic decision-making skills.

SEI's competitive advantage:


To help you stay energized, engaged and inspired, we offer a wide range of benefits including comprehensive care for your physical and mental well-being, a strong retirement plan, tuition reimbursement, support for working parents and flexible Paid Time Off (PTO) so you can relax, recharge and be there for the people you care about.


Benefits include healthcare (medical, dental, vision, prescription, wellness, EAP, FSA), life and disability insurance (premiums paid for base coverage), 401(k) match, education assistance, commuter benefits, up to 11 paid holidays/year, 21 days PTO/year pro-rated for new hires which increases over time, paid parental leave, back-up childcare arrangements, paid volunteer days, a discounted stock purchase plan, investment options, access to thriving employee networks and more.


We are a technology and asset management company delivering on our promise of building brave futures (SM)-for our clients, our communities, and ourselves. Come build your brave future at SEI.


The position title reflected in this job description is aligned with SEI's current internal job architecture. As part of SEI's role and career framework, internal job titles may not directly correspond to external market titles and may differ from titles previously assigned during an employee's tenure or at the time of hire.


SEI is an Equal Opportunity Employer and so much more...


After over 50 years in business, SEI remains a leading global provider of investment processing, investment management, and investment operations solutions. Reflecting our experience within financial services and financial technology our offices encompass an open floor plan and numerous art installations designed to encourage innovation and creativity in our workforce. We recognize that our people are our most valuable asset and that a healthy, happy, and motivated workforce is key to our continued growth. At SEI, we're (literally) invested in your success. We offer our employees paid parental leave, back-up childcare arrangements, paid volunteer days, education assistance and access to thriving employee networks.


SEI is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law.


AI Acceptable Use in the application and interview process:


SEI acknowledges the growing integration of artificial intelligence (AI) tools into individuals' personal and professional lives. If you intend to incorporate the use of any AI tools at any stage of the application and/or interview process, please ensure you have reviewed and adhere to our AI use guidelines.


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