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Machine Learning Engineer

Ikigai Labs

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.


  • 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


  • 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


  • 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