Design, develop, and deploy machine learning models; analyze large datasets; build scalable data pipelines and distributed computing environments; integrate ML solutions with cross-functional teams; optimize performance and support production ML infrastructure.
Machine Learning Engineer
We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity to shape and create our machine learning capabilities from the ground up. You'll be at the forefront of innovation, designing and implementing ML systems that drive our business forward.
Responsibilities:- Design, develop, and implement machine learning models and algorithms
- Analyze large datasets and extract meaningful insights
- Collaborate with cross-functional teams to integrate ML solutions into existing systems
- Optimize ML models for performance and scalability
- Stay current with the latest advancements in machine learning and AI
- Create and implement big data processing pipelines and architectures
- Design and build scalable data infrastructure to support ML applications
- US Citizen
- Bachelor's or Master's degree in Computer Science, Data Science, or related field
- 3+ years of experience in machine learning or AI development
- Strong proficiency in Python and its ML/data science libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas)
- Solid understanding of machine learning algorithms and statistical modeling
- Experience with big data technologies (e.g., Hadoop, Spark, Kafka)
- Proven ability to create and implement big data solutions from scratch
- Comfortable setting up and managing distributed computing environments
- Experience in designing and implementing data pipelines for large-scale data processing
- Proficient in working with various database systems, both SQL and NoSQL, depending on the use case
- Strong skills in data modeling and database design for machine learning applications
- Excellent problem-solving and analytical skills
- Strong communication skills and ability to work in a team environment
- Experience in creating and managing real-time data streaming architectures
- AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty
- Experience with AWS machine learning services
- Proficiency in using AWS big data services
- Knowledge of serverless architectures on AWS (e.g., Lambda)
- Experience in creating and managing real-time data streaming architectures on AWS (e.g., Kinesis)
- Understanding of AWS security best practices for machine learning and data processing workflows
- Be a member of a world-class team focused on inventing solutions that have the ability to impact the world
- Tackle a wide variety of technical problems throughout the stack and contribute daily to all parts of our product code base
- Help build a beautiful, intuitive product that revolutionizes the nonprofit industry
- Work closely with our customers, founders, team members and Board to understand customer pain points, develop solutions, and prototype, iterate, and deploy code on regular cycles
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What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
