| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
MoonPay | Barcelona, Spain | $126k - $127k | |||
Rome Protocol | westlake village, ca, usa | $9000k - $15000k | |||
Coinmarketcap | Taipei, Taiwan | $105k - $106k | |||
Fireblocks | Get a Fireblocks Platform Demo | $98k - $150k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Syndica | Dubai, United Arab Emirates | ||||
Chainlink Labs | United Kingdom | $122k - $150k | |||
Chainalysis | United Kingdom | $90k - $100k | |||
Caldera | United States | $103k - $106k | |||
Ledger | Paris, France | $120k - $156k | |||
Overclock Labs | Austin, TX, United States | $80k - $95k | |||
DIA e.V. | Remote | $64k - $80k | |||
Status | Remote | $63k - $150k | |||
Brave | San Francisco, CA, United States | $126k - $127k | |||
Keyfactor | Remote | $105k - $106k | |||
BitGo | Toronto, Canada | $180k - $240k |
Machine Learning Engineer
What you will do
- Consult with data scientists on training machine learning models (after all, in a production environment, there are implications to model choices that need to be considered)
- Provide a strategic vision on how to make machine learning a cornerstone to MoonPay’s business
- Support additions and improvements to the ML infrastructure, including getting your hands dirty with data engineering and DevOps engineering
- Design systems to meet throughput and latency requirements
- Implement NFRs (Non-Functional Requirements) to ensure a high degree of system reliability
- Implement and participate in practices (such as an on-call rotation) to ensure the continuous delivery of machine learning services
- What you will need…
- Prior experience with productionising ML systems is a must.
- Prior experience training machine learning models is highly desirable.
- Advanced knowledge of Python and familiarity with SQL.
- Good working knowledge of Terraform and Terragrunt for Infrastructure as Code (IaC)
- A solid understanding and hands-on experience with real-time and event-driven systems such as Kafka, Kafkaconnect, Redpanda, Pub/Sub.
- Solid experience with Kubernetes, docker, deployment types (canary, blue-green etc.)
- Experience with setting up CI/CD systems using tools such as CircleCI, drone, Github actions, ArgoCD.
- Working experience with Big Data technologies such as Spark, Dataflow, and Flink.
- Experience with system design - keeping performance and efficiency in mind, whilst aware of trade-offs.
- Experience applying software engineering rigor to ML, including CI/CD/CT, unit-testing, automation etc.
- Hands-on experience with some MLOps tools such as KubeFlow, DVC, MLFlow.
- Experience with cloud providers, such as GCP, AWS, or Azure (we are a GCP house)
- Prior experience or a strong interest in FinTech, crypto, or web3 preferred.
Is Kubernetes high demand?
Yes, Kubernetes is currently in high demand in the technology industry
Kubernetes is an open-source container orchestration platform that is widely used for deploying, scaling, and managing containerized applications
It provides a standardized way to manage and automate the deployment of containerized applications across multiple hosts and provides benefits such as reliability, scalability, and flexibility
As more and more organizations move towards containerized architectures, Kubernetes has become a critical component of their infrastructure
Kubernetes is used by companies of all sizes, from startups to large enterprises, and across various industries, including finance, healthcare, and e-commerce
According to various job market and salary surveys, Kubernetes-related skills are in high demand, and job positions related to Kubernetes are growing at a rapid pace
In fact, Kubernetes is often listed as one of the top skills that are in high demand by technology companies
Overall, Kubernetes is a highly sought-after skill in the technology industry, and it's likely to remain in high demand in the foreseeable future as more and more organizations adopt containerization and cloud-native architectures.