Sr. Software Engineer


Posted: 02/01/2023 Job Number: 20664

Job Description

Senior Machine Learning Engineer                                                                             



We are currently seeking a Senior Machine Learning Engineer. They will service all of data science team.

This position will be remote. Preferably in same time zone, but flexible. 

Job Summary

As a Senior Machine Learning Engineer you will act as a primary contributor within the development initiatives for the team. You will own the end-to-end architecture and deployment of data pipelines, various types of models, and delivery of our team’ s machine learning solutions.
  • Experience with MLOps, developing and automating scalable machine learning pipelines in cloud ecosystems (Azure/AWS/GCP)
  • Experience with data warehousing systems, data systems integration, and cloud data solutions including data lakes or managed services like Snowflake or Databricks
  • Experience with CI/CD tools (e.G., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent)
  • Expertise with in Python and SQL across a variety of platforms
  • Knowledge of Data Science and Machine Learning development tools and processes (TensorFlow, PyTorch, Scikit-learn, MLFlow, DVC, etc.)
  • Familiarity with applied data science methods, feature engineering and machine learning algorithms
  • Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required
  • Experience containerizing models using Docker and managing deployment through Kubernetes
  • Experience designing reusable APIs for model deployment for downstream consumption
  • Experience designing model monitoring systems (Grafana, Alibi Detect)
  • Ability to develop clear documentation for business partner management across audiences with multiple levels of technical skills


Nice to have
  • Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’ s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.)
  • Experience with building data pipelines in getting the data required to build and evaluate ML models
  • Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies
  • Experience with designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models

  • As a Senior Machine Learning Engineer you will act as a primary contributor within the development initiatives for the team
  • Own the end-to-end architecture and deployment of data processing, model execution, and delivery of our team’ s machine learning solutions
  • Build infrastructure for training, deploying, versioning, monitoring, and updating a suite of deep learning models in production
  • Participate as a subject matter expert across the domains of data science, computer science, and machine learning
  • Extend existing ML Platform and frameworks for scaling model training & deployment
  • Building advanced analytics solutions using various cloud technologies and collaborating with Data Scientists to robustly scale up ML Models
  • Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics

Other Knowledge, Skills or Abilities Required 
  • Strong written and oral communication skills with ability to work with users, peers, and management.
  • Strong interpersonal skills.
  • You have the ability to deal with ambiguity and work in fast paced environment
  • Ability to work independently and as part of a team to successfully execute projects.
  • Highly motivated, self-starter with problem solving skills.
  • Ability to multitask and meet aggressive deadlines efficiently and effectively.
  • Detail-oriented but does not lose sight of the big picture.
  • Demonstrate ability to learn and understand business processes quickly
Duration: 1 year; will consider extension based on performance and budget.
Interview format:
-30 minute Phone screen: Basics and personality 
-1 hour Technical interview/Meeting the team
-Only a 3rd round if tie breaker candidates

Meet Your Recruiter

Shane Readyhough

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