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
