Machine Learning Engineer
Ikigai Labs
Software Engineering
Cambridge, MA, USA
Posted on Thursday, September 7, 2023
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