Machine Learning Engineer

Key Responsibilities

• ML Optimization and Deployment: Develop and deploy machine learning models for optimal performance and scalability
• Productivity Tools Development: Build tools and services to enhance the ML platform, utilizing technologies like Kubernetes, Helm, and EKS
• Model Architecture: Apply a strong understanding of deep learning architectures (CNNs, RNNs, etc.) to solve complex problems
• Research Adaptation: Stay abreast of recent ML and deep learning literature and adapt findings to real-world applications
• Collaborative Development: Work with cross-functional teams to integrate AI and ML solutions that drive business value
• Data Handling: Manage large datasets and build ML pipelines for data processing and training
• ETL/ELT Processes: Design and develop scalable data integration processes
• Predictive Modeling Platform: Develop an on-demand predictive modeling platform using gRPC
• Cloud and Containerization: Utilize Kubernetes for managing Docker containers and various cloud services (AWS, Azure) to solve cloud-native challenges
• Stakeholder Management: Provide occasional support to our customer success team

Qualifications

• Bachelor’s degree in Computer Science, Math, Engineering, or related field (Master's preferred) with 0-5+ years of experience (depending on the level)
• Strong understanding of data structures, data modeling, algorithms, and software architecture
• Proficient in probability, statistics, and algorithm development
• Hands-on experience with ML and deep learning libraries (Scikit Learn, Keras, TensorFlow, PyTorch, Theano, DyLib)
• (Bonus) Experience with big data and distributed computing (Hadoop, MapReduce, Spark, Storm)
• Proficiency in Python, AWS services, and ETL/ELT pipelines
• Understanding of key software design principles, design patterns, and testing best practices
• Experience with Kubernetes and/or EKS is a plus
• Able to learn quickly in a fast-paced, agile environment
• Excellent organizational, time management, and communication skills
• Willingness to engage in pair programming, share knowledge, and provide and receive constructive feedback
• Strong problem-solving skills and the ability to take initiative