Ikigai Labs seeks a dynamic and passionate engineer with strong software fundamentals to join a high-performing Machine Learning team. We are looking for a team player who is a quick learner, performs in a rapid development cycle, has a drive to surpass expectations, and an eagerness to share their work and knowledge.

We encourage applicants from all backgrounds and communities. We are committed to having a team that is made up of diverse skills, experiences, and abilities.

ROLE:

• Optimize and deploy ML solutions for maximum performance and scale
• Build productivity tools and services for the ML platform, which includes working on various tools like Kubernetes, Helm, EKS etc
• Strong understanding of deep learning model architectures such as convolutional, residual, attentional, and recurrent neural networks
• Ability to understand recent ML and deep learning literature and adapt those models to solve real world problems
• Work collaboratively to develop and integrate AI and machine learning that deliver on business value
• Work with large datasets and build a ML pipeline to process and train the data
• Design and develop scalable data integration (ETL/ELT) processes
• Design and develop an on-demand predictive modeling platform with gRPC
• Utilize Kubernetes to orchestrate the deployment, scaling and management of Docker containers
• Utilize and learn various Cloud services - AWS, Azure etc to solve cloud-native problems
• Provide periodic support to our customer success team

TECHNOLOGIES:

• Languages: Python3, C++, Rust, SQL
• Frameworks: PyTorch/TensorFlow, Docker
• Databases: Postgres, Elasticsearch, DynamoDB, RDS
• Cloud: Kubernetes, Helm, EKS, Terraform, AWS
• Data Engineering: Apache Arrow, Dremio, Ray
• Misc.: Git, Jupyterhub, Apache Superset, Plotly Dash

QUALIFICATIONS:

• 1-3 years of experience with a bachelor's degree in Computer Science, Math, or Engineering; or a master's degree in related field
• Understanding of data structures, data modeling, algorithms and software architecture
• Knowledge of probability, statistics and algorithms
• Experience with Machine learning and Deep learning libraries such as: Scikit Learn, Keras, TensorFlow, PyTorch, Theano, or DyLib
• (bonus) Experience with big data and distributed computing technologies such as: Hadoop, MapReduce, Spark, and Storm
• Experience with Python, AWS services, and/or ETL/ELT pipeline experiences
• Understanding of key software design principles
• Experience with Kubernetes and/or EKS (optional)
• Understanding of the fundamentals of design patterns and testing best practices
• The ability to learn quickly in a fast-paced environment
• Excellent organizational, time management, and communication skills
• The desire to work in an AGILE environment with a focus on pair programming
• Willingness to discuss obstacles, find creative solutions, and take initiative
• The ability to receive and give both constructive and encouraging feedback