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ML Ops Engineer

4 months ago

Providence, United States Saxon Global Full time
Machine Learning Ops Engineer

The position:

Apex is seeking a seasoned Consultant with strong consultative skills to act as a Machine Learning Ops Engineer within Apex Systems Consulting Services. This role will serve on project teams with Apex clients to design and deliver enterprise machine learning solutions focusing on automating and scaling the machine learning model lifecycle (including governance and "MLOps"). This role will also provide technical subject matter expertise for Apex sales and account teams during the scoping of new machine learning-based opportunities.

Responsibilities:
  • Lead the design, delivery and validation of applications and pipelines to automate the curation of data, train and validate models, and deploy and govern machine learning solutions in a production environment
  • Coordinate with data scientists and DevOps engineers to improve the coordination between the two teams within the enterprise ML environment
  • Advise clients and implement solutions addressing performance, scalability, and the governance/traceability of machine learning models
  • Build strong client, industry, and technical community relationships and represent Apex Systems as leaders in Industry and Professional events and communities. Develop and maintain strong internal and external customer relationships
  • Demonstrate strong technical knowledge and implementation skills. Stay current on relevant technology trends and practices. Build trust and respect among internal and external stakeholders and demonstrate collaborative teamwork
  • Produce high quality deliverables, meet project deadlines, and take responsibility for engagement success. Demonstrate a passion for quality and process improvement
  • Demonstrate professional level consulting skills and communication/presentation skills. Demonstrate adaptability and flexibility to acquire skills to meet business needs
  • Continually innovate, seek creative solutions, and find new ways of adding value. Listen and seek to understand the client and meet their needs, providing consultative guidance. Stay attuned to the future needs of the client and work with internal resources to identify opportunities. Proactively provide solutions and approach adversity with a solution-focused mindset
  • Identify and evaluate new team members through professional networking and technical screening
Experience:
  • 7+ years of experience in application/software development with 3-5 years combined experience delivering DevOps and Machine Learning solutions (a.k.a. "MLOps") in a Production/Enterprise setting
  • Experience working with teams of developers and other technical professionals in an Agile delivery framework
  • Proficient with the machine learning modelling lifecycle and comfortable addressing both functional and technical aspects of model delivery
  • Positive relationship builder able to navigate through complex situations to ensure the most robust and pragmatic solution
  • Strong analytical skills and the aptitude to quickly identify gaps and risks
  • Excellent written and spoken communication skills, including the ability to present complex concepts to engineering and business partners
  • BA/BS required, preferably in Computer Information Systems, Computer Science, or related fields (applicable education and experience may be substituted)
  • Advanced degree (MS) in a quantitative discipline preferred (applicable experience may be substituted)
Technical Requirements:
  • Expertise with standard Machine Learning frameworks such as Tensorflow, Keras, PyTorch and/or sk-learn
  • Proficient programming with languages such as Python, Java and/or Scala
  • Adept at leveraging Cloud platforms and tools like Azure Machine Learning, MLFlow, Kubeflow, Databricks, and/or Amazon Sagemaker
  • Proficiency with DevOps tools including Terraform, Git-flow, Azure Resource Management Templates ("ARM Templates"), Azure DevOps, Docker and/or Kubernetes
  • Good working knowledge of relational databases like Snowflake, SQL Server, Amazon Redshift, Delta Lake, and NoSQL databases (Azure CosmosDB, for example)
  • Successful working in an Agile, scrum-based environment where defining concise user stories and collaborating with stakeholders is key
  • Azure or AWS certifications applicable to architecture, DevOps and/or engineering preferred

Required Skills : Databricks Python ML Frameworks
Basic Qualification :
Additional Skills :
Background Check :Yes
Notes :
Selling points for candidate :
Project Verification Info :
Candidate must be your W2 Employee :No
Exclusive to Apex :No
Face to face interview required :No
Candidate must be local :No
Candidate must be authorized to work without sponsorship ::No
Interview times set : :No
Type of project :Development/Engineering
Master Job Title :AI: Machine Learning Dev/Eng
Branch Code :East Bay