Machine Learning Engineer, Specialist
Tasks
- Align research priorities with business needs
- Build prototypes and proof of concept systems
- Conduct advanced AI research
- Design practical AI solutions
- Develop new AI algorithms and models
- Ensure AI safety and risk mitigation
- Follow Responsible AI principles
- Guide research writing and technical direction
- Mentor junior scientists and engineers
- Present findings at conferences and internal forums
- Publish research in top-tier conferences and journals
- Transition research to scalable production systems
Perks/Benefits
- Financial wellness programs
- Hybrid work model
- Personal wellness resources
- Physical wellness benefits
- Wellness support
Skills/Tech-stack
Agent Orchestration | Agentic AI | Attention | Containerization | DPO | Deep learning | DeepSpeed | Distributed Training | Experiment tracking | FSDP | Fine Tuning | GPU Training | Instruction Tuning | LLM Observability | Langfuse | Langsmith | Language Models | Large Language Models | Low-Rank Adaptation | MLflow | Model Monitoring | Model Serving | Multi-Agent | Multi-GPU | Multi-GPU Training | Multi-agent orchestration | Online evaluation | PEFT | Planning | Prompt engineering | PyTorch | Python | RAG | RLHF | Regression testing | Responsibile AI | Retrieval-Augmented Generation | TGI | Tool use | Transformer | VLLM | Weights and Biases
Education
Master of Engineering | Master of Science | PhD | Post Doctorate
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