Senior ML Infrastructure Architect
We are a fast-growing and pioneering people analytics company that is transforming the financial workplace. We use cutting-edge software and machine learning to generate previously unidentifiable insights into employee behavior and performance. We have been recognized by renowned companies such as Amazon Web Services and Google Cloud for our achievements in AI, big data analytics, and machine learning. We have also been included in the Forbes FinTech 50, CB Insights AI 100, and Tech Nation’s prestigious Future 50 program.
Our goal is to help businesses achieve better outcomes by developing and delivering data-driven solutions for compliance, CRM, HR, and workplace productivity. We also aim to rapidly expand our worldwide customer base to include companies across all major industries.
About the role
Building the right AI/ML Infrastructure means making the right decisions that support the ongoing cutting edge research, development, testing and shipping of AI/ML models to production. We are looking for builders, makers and hackers that will not just help build our AI serving Infrastructure but take the domain to the next level. You will be touching tools like Airflow, MLflow, Docker while building a scalable serving infrastructure for machine learning models built with frameworks like pyTorch and TensorFlow. You will be pushing the limits of our infrastructure and of Artificial Intelligence.
Ideal candidate profile
- Enterprise-level architect experience building/shipping large scale microservices infrastructure
- Strong Python and enterprise Java programming experience
- Experience in building, designing, and hacking high-load distributed data processing systems, preferably involving search, NLP, graphs or other related machine learning related domains
- Experience building and scaling python microservice based application / infrastructure using technologies like Docker, Redis, Kafka, RabbitMQ etc
- Understanding of DevOps culture (CI/CD, Ansible, Jenkins)
- Familiar or willingness to learn more about python machine learning ecosystem, numerical optimization libraries, like numpy, pandas, dask, cython, numba, pybind11, tensorflow, pytorch
What we offer
- A highly accomplished and global team
- Competitive salary
- Bonus for overachieving KPIs
- Fully covered health benefits
- Training and mentoring opportunities
- HR phone interview to discuss your skills, experience, and interests
- Interview with the hiring manager
- Take-home technical task
- Final on-site interview with ML Team members and Chief Data Scientist