Senior MLOps Engineer
2 tygodni temu
Emerging Tech Developers create rapid proofs of concept to test hypotheses about how emerging technologies can be applied to business use cases. We learn and explore at the forefront of Artificial Intelligence, Blockchain, Internet of Things, Robotics, Virtual Reality and Augmented Reality. The lab’s role is to generate prototypes, demos and learnings that our teams and clients can use when deciding how to apply and invest in emerging technologies.
The majority of the resources would be supporting the development of assets (e.g., plugins) to further drive our overall AI strategy across the firm. In addition to that, we have ongoing AI R&D initiatives that we’d look to leverage some of these roles to help us continue driving the initiatives.
Expected start date: ASAP
Remote vs Onsite: Remote, with possible occasional in person team sessions / workshops / gatherings (i.e. 1x quarter) likely to take place in office
HackerRank challenge: Yes
Senior MLOps Engineer - US AI Services
Your responsibilities
- The Senior MLOps Engineer will be responsible for designing, developing, and operationally implementing machine learning projects. This role requires a combination of engineering, automation, and data science skills to support scalable ML solutions.
Our requirements
- Proven experience in programming with languages such as Python, GO, or similar.
- Hands-on experience with one or more cloud computing platforms (Azure - preferred, AWS, GCP).
- Extensive experience in architecting and implementing end-to-end operations for machine learning projects.
- Proven experience in designing and implementing CI/CD/CL pipelines for machine learning projects.
- Hands-on experience with serverless functions and DevOps tools for building and automating pipelines.
- Experience with containers (Docker) and their orchestrations (Kubernetes).
- Experience with Infrastructure as Code. Terraform is a plus.
- Proficiency in RDBMS/NoSQL data stores and appropriate use cases.
- Proficiency in machine learning libraries such as scikit-learn, TensorFlow, Keras, PyTorch, and Spark MLlib is a big plus.
- Experience with orchestrated Large Language Model (LLM) applications is a plus.
- Ability to create and deploy technology prototypes and machine learning models for business applications is a plus.
- Experience with rapid prototyping and agile methodologies.
- Effective communication skills to present technical solutions to business audiences.
- Interest and knowledge in emerging technologies is a plus.
- Previous experience in an innovation lab or similar environment is advantageous.
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