Senior Machine Learning Engineer

2 weeks ago

Boston, United States Barrington James Full time

Barrington James is currently seeking a Senior Machine Learning Engineer for one of its clients dynamic teams based in Boston. The ideal candidate will possess a proven track record in advancing, expanding, and refining the framework of a rapidly evolving product. Our client value a commitment to development, instruction, learning, and engagement within a high-achieving, interdisciplinary team dedicated to impacting the healthcare experience of countless patients and medical professionals.


Key Responsibilities:

  • Architect, develop, and sustain the infrastructure pivotal to our machine learning applications, services, and processes.
  • Construct, uphold, and augment our ML platform, facilitating continuous integration, delivery, and training of our machine learning models.
  • Utilize advanced programming languages, cloud-based services, and serverless architectures to forge systems that are both scalable and robust.
  • Conceptualize, design, and forge components within the data pipeline to empower a variety of machine learning models in a live environment.
  • Spearhead the creation and execution of infrastructure initiatives, including the formulation of technical blueprints, strategies, and detailed specifications, as well as their ongoing refinement.
  • Design, implement, and manage the comprehensive ML platform stack, encompassing features like monitoring, data observability, and the entire model lifecycle.
  • Examine the current pipeline, pinpoint inefficiencies, and enhance both the throughput and response times of ML elements.
  • Harmonize performance indicators and notifications with fiscal prudence and precision.
  • Craft and deploy automated mechanisms for model training and deployment.


Requirements:

  • At least 4 years of expertise in ML Systems Engineering.
  • A minimum of 4 years of professional experience in Python (preferred) or other prevalent languages within the ML sphere.
  • Expertise in the inference optimization of NLP models.
  • Solid proficiency with infrastructure and DevOps instruments, including Kubernetes, Docker, and Ansible.
  • Familiarity with distributed systems, storage solutions, and databases.
  • In-depth understanding of cloud services platforms like AWS (preferred), GCP, and Azure.
  • Experience with code-based infrastructure tools such as Terraform (preferred), Pulumi, Cloud Formation, etc.
  • Knowledge of monitoring, tracing, and logging utilities like Cloudwatch, NewRelic, Prometheus, etc.
  • Exceptional communication abilities, a robust sense of responsibility, and a methodical problem-solving approach.
  • Demonstrated capacity to oversee and direct active incidents, determine their origins, and devise strategies to prevent future occurrences.


Interested ? If so, please apply with your CV and we shall be in-touch to arrange a call.

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