Senior Machine Learning Engineer 

valeria voloshchuk

Published: 21 Jun, 2024

We are seeking a skilled and experienced ML Engineer to join our client’s team.  

Client – startup funded and contracted by the DoD. Sponsored to develop several Prototype Projects to be rolled out to Agencies and Entities in the Govt and the Critical Infrastructure sectors. Some of these projects involve among others creating a global network of GPU and High Compute CPU enabled data centers globally to be used for both military (Missile Defense) and Civilian usage (Meta verse, Smart Cities, 6G enabled tools and applications), and supporting AI and ML workloads for Critical Infrastructure sector. 

HQ – USA, New-York 


  • Proven previous experience in Machine Learning 
  • Experience in design and evaluate MLOps pipelines, ensuring secure workflows from deployment through governance and monitoring 
  • Familiar with working with legacy models as well as foundational models and concepts of training, federated learning, model versioning fine-tuning etc 
  • Experience in improving the performance of large language models (LLMs) 
  • Experience with CUDA, Python, DataBricks, PyTorch, Hugging Face 
  • Familiarity with model quantization, synthetic data ingestion, and advanced optimization and benchmarking techniques 
  • Proficiency in English (verbal and written) 


The Engineers will be responsible for creating and evaluating the MLOPS pipeline and securing the workflow from deployment to governance and monitoring. The Engineers will also be required to optimize the performance of LLM Models 

Also, will take part in the next projects:  

  • Create NVIDIA/VMWARE/REDIS-based Operating System deployment 
  • Build out a RAG based knowledge-based system to be able to ingest different types of data (text, logs, media data) 
  • Develop fine-tuned customer service LLM agents that can provide vocal and 1st second-layer support 
  • Realtime Network Anomaly Detection through foundational models. 

We offer:

  • Flexible working schedule, remote work opportunities 
  • Vacation (up to 20 working days) + paid day offs on National Holidays  
  • Paid sick leaves (10 working days) 
  • Direct cooperation with the customer 
  • Great working environment and team spirit 
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