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.
In order to make an application, simply read through the following job description and make sure to attach relevant documents.
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
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