Senior MLOps Engineer with ODAIA

Remote (United States)

$140K - 170K a year

ODAIA nouno·da·ia | \ 'oh-day-yeah \ An Ancient Greek word referring to a salesperson's “tools of the trade.”

Learn more about our company here. You can also find more information about the company and our products at odaia.ai.

ODAIA is a remote first organization, all our positions are WFH.

ODAIA helps pharma sales and marketing teams by using AI to understand and predict customer behaviour. Our enterprise SaaS product MAPTUAL serves some of the most recognized Fortune 500 life sciences companies. By incorporating data and AI predictions in powerful ways, MAPTUAL's users understand their customers (healthcare professionals, patients) on a deeper level and cater to their health needs more effectively.

ODAIAns (what we call ourselves) are inspired to reinvent the future of how non-technical people leverage data in their day-to-day lives. We are passionate about solving complex problems in data, AI, engineering, design, and product, so our customers don't have to. We live by the notion that “simplicity is the ultimate sophistication;” and making simplicity scalable is an even bigger challenge. That's why we have a crazy talented team led by serial entrepreneurs, tech veterans, and life sciences experts.

Our mission

Reducing patients' time to therapy by facilitating meaningful interactions with healthcare providers, through human-centric software powered by AI.

We're also on a mission to build an innovative, diverse, and ego-free business, where trust, innovation and ownership are valued. You're on a mission too? We're here for it. We put an emphasis on career development for our employees, and the opportunities to grow are extensive.

What's on offer

Reporting to the Machine Learning Data Scientist Development Manager, the Senior MLOps Engineer is experienced, creative and passionate about building best practice Machine Learning pipelines and operations. The successful candidate will work closely with other feature teams; collaborating cross-functionally throughout the development process to ensure the product is functionally complete and technically solid. This is an excellent opportunity to join a rapidly growing innovator in a technically challenging and rewarding role. \n

WHAT YOU WILL DODesign and implement efficient and reliable solutions / architectures to serve our Machine Learning products/workflowCollaborate with our Data Engineering and ML Engineering teams to understand the current pain points in the workflow for performance optimizationImplement standard best practices in Machine Learning model management and deploymentHelp the intermediate and junior engineers in breaking down the solutions for more efficient implementation, and deploymentExpert on AWS cloud platform and the provided Machine Learning platforms / solutions such as SageMakerExplain complex architecture and ML concepts to technical and non-technical audiencesContinue to develop our learning and growth culture

WHAT YOU BRINGExpert knowledge and experience in all steps of industry-level machine learning workflow from data preparation to model management and deploymentProficiency in various machine learning libraries (i.e., Scikit-Learn, XGBoost, TensorFlow or Pytorch, etc.)Solid understanding new ML and MLOps strategies and their implementation on the cloud (i.e., Kubernetes and Kubeflow)Proficiency in software development (i.e., advanced topics, OOP, etc.) using PythonStrong background in AWS solutions for Machine Learning such as SageMakerKnowledge and experience in Docker and model deployment on AWSFamiliar with implementation of REST API (i.e., Fast API in Python)Able to frame data-driven solutions to solve business problemsGood communication skills to explain the solutions and guide the team

WHAT WE OFFERA highly productive driven startup culture that values agility, passion, ownership, trust, respect, diversity and inclusionTremendous growth and unique learning opportunitiesA large amount of ownership and autonomy for managing things directlyAn inclusive environment, we are an equal opportunities employer and we operate with an anti-oppression mindsetTop-notch health benefits for medical, dental, vision care, mental health, prescription drug coverage, travel insurance and alternative treatments such as acupuncture and chiropractic servicesFlexible working hours, providing great balance for personal and family lifeWe focus on what we achieve and not the number of hours we clockWe trust our employees and empower them to shape their work themselves so that they can achieve the best possible resultsAn open and flexible vacation policyOur employees can take what they want, when they want it - as long as they get their work done, get the time approved and get things covered while they're awayStock option grantsA generous home office allowanceCareer development opportunities, and a solid business model - we're in it for the long haul!

\nIf you think you may not check every box, don't worry, we would love to see your resume anyway! Odaians are at core a group of great and talented people, eager to learn, take ownership, and turn ambitious ideas into reality.

Location

We are a remote-first company based in Toronto with frequent in-person collaborative work sessions and social gatherings at a work-share office in downtown Toronto. We leverage many synchronous and asynchronous communication tools as well as virtual social events, and provide an allowance for your ideal WFH setup.

Employment verification

Any conditional offer of employment made to a successful candidate will be subject to the full satisfaction with the results of any background and reference checks.

Accommodations and accessibility

Accommodations are available on request for candidates with disabilities taking part in all aspects of our hiring process. For more on this, you can inquire about accommodations if you're invited to an interview.

Responsibilities

  • Design and implement efficient and reliable solutions / architectures to serve our Machine Learning products/workflow
  • Collaborate with our Data Engineering and ML Engineering teams to understand the current pain points in the workflow for performance optimization
  • Implement standard best practices in Machine Learning model management and deployment
  • Help the intermediate and junior engineers in breaking down the solutions for more efficient implementation, and deployment
  • Expert on AWS cloud platform and the provided Machine Learning platforms / solutions such as SageMaker
  • Explain complex architecture and ML concepts to technical and non-technical audiences
  • Continue to develop our learning and growth culture

Requirements

  • Expert knowledge and experience in all steps of industry-level machine learning workflow from data preparation to model management and deployment
  • Proficiency in various machine learning libraries (i.e., Scikit-Learn, XGBoost, TensorFlow or Pytorch, etc.)
  • Solid understanding new ML and MLOps strategies and their implementation on the cloud (i.e., Kubernetes and Kubeflow)
  • Proficiency in software development (i.e., advanced topics, OOP, etc.) using Python
  • Strong background in AWS solutions for Machine Learning such as SageMaker
  • Knowledge and experience in Docker and model deployment on AWS
  • Familiar with implementation of REST API (i.e., Fast API in Python)
  • Able to frame data-driven solutions to solve business problems
  • Good communication skills to explain the solutions and guide the team