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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Solution Architect - **Company:** Cencora - **Location:** Philadelphia, PA, United States - **Experience:** Expert - **Salary:** $150,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Amazon Web Services, Data Analysis, Data Security, Python (Programming Language), Machine Learning, Scala (Programming Language), Software Engineering, Data Storage Technologies, Feature Engineering, Snowflake, Apache Spark, Information Technology, Data Pipelines, Api Management - **Published:** July 5, 2026 - **Apply:** https://www.careerjet.com/job/usd743a310f27ca37becc60e94bd10fd8a/eaa ## About the Role * Bachelor's degree in Computer Science, Information Technology, or a related field. Master's degree or PhD will be a plus. * Minimum of 6 years of experience as a Machine Learning Engineer or similar role. * Demonstrated experience with ML Model, AWS, Python, Scala, Data pipelines, Spark, Snowflake, and consulting. * Proven experience in designing and implementing machine learning solutions at scale on AWS. * Solid experience in software development with a focus on quality, performance, and scalability. * Proven ability to design and implement robust data pipelines. * Strong experience with data modeling, data access, and data storage techniques. * Excellent communication skills with the ability to effectively convey complex technical concepts to non-technical stakeholders. * Strong problem-solving skills, attention to detail, and ability to think creatively. * Ability to work independently and as part of a team in a fast-paced, dynamic environment. * Strong passion for learning and adapting to new technologies. * AWS Certified Machine Learning or similar certification will be a plus. ## Description We are seeking a dynamic and innovative Machine Learning Solution Architect to join our team. This role is a unique opportunity to join a passionate and mission-driven team that is building a 100 million dollar company looking to quadruple in scale. The successful candidate will be responsible for developing and implementing machine learning models, utilizing AWS, Python, Scala, and other technologies to design and develop data pipelines. The role requires a deep understanding of Spark, Snowflake, and experience consulting. The candidate should have a minimum of 6 years of experience in a similar role., * Design, develop, and implement end-to-end cloud-based machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation). * Ensure the robustness, scalability, and enterprise-level security of solutions. * Collaborate with the data science team to transform prototypes into new products, services, and features. * Build and maintain data platforms for machine learning model development, ensuring that data is readily available for insight generation. * Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity. * Collaborate with cross-functional teams to understand their business needs and proactively suggest / implement solutions to leverage technology and data. * Provide thought-leadership and consulting services across the business, leading internal teams in the application of ML techniques and practices. * Stay up-to-date with the latest industry trends and technologies to ensure the team is utilizing the best techniques and tools., Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. Information collected and processed as part of your Jobot candidate profile, and any job applications, resumes, or other information you choose to submit is subject to Jobot's Privacy Policy, as well as the Jobot California Worker Privacy Notice and Jobot Notice Regarding Automated Employment Decision Tools which are available at jobot.com/legal. By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here: jobot.com/privacy-policy ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation](https://www.wearedevelopers.com/videos/612-fireside-chat-deep-learning-deep-impact-harnessing-ai-for-language-innovation) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)