Job description

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 Requirements: • 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 Preferred Qualifications: • 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 What you’ll do day-to-day: • 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

Requirements

Must-haves

Machine Learning Engineer
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
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

Nice-to-haves

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

Application prep

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Keywords to mirror

machine learningaimlpythonsqlaws

Platform: breezy
Effort: medium