over 1 year ago
Remote, United StatesMid Level
Responsibilities
- Design, develop, implement, and optimize machine learning models and algorithms.
- Analyze large datasets and extract meaningful insights.
- Integrate ML solutions into existing systems with cross-functional teams.
- Create big data processing pipelines and scalable data infrastructure for ML applications.
- Set up and manage distributed computing environments.
- Design and implement data pipelines for large-scale processing.
- Develop real-time data streaming architectures and AWS-based data solutions.
- Contribute across the product codebase, prototype and deploy solutions, and address customer pain points.
Requirements
- Must be a US Citizen.
- Bachelor’s or master’s degree in Computer Science, Data Science, or a related field.
- At least 3 years of experience in machine learning or AI development.
- Strong proficiency in Python and ML/data science libraries including TensorFlow, PyTorch, scikit-learn, and pandas.
- Strong understanding of machine learning algorithms and statistical modeling.
- Experience with Hadoop, Spark, Kafka, SQL, NoSQL databases, data modeling, and database design.
- Proven ability to create big data solutions from scratch and design large-scale data pipelines.
- Ability to manage distributed computing environments and work across the technology stack.
- Strong problem-solving, analytical, communication, and teamwork skills.
- Preferred: AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty.
- Preferred: experience with AWS machine learning and big data services, Lambda, Kinesis, serverless architectures, streaming architectures, and AWS security best practices.
Tech Stack
Categories
Data EngineeringML Engineering
About Givzey
Givzey builds fundraising software for nonprofits, schools, and universities. Its SaaS platform includes a standalone Gift Agreement product that lets fundraisers generate and secure gift commitments in seconds, plus tools that turn donor data into automated outreach and pledges. Headquartered in Boston and privately held, the company serves higher-education and nonprofit development teams.