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ML Practice Leader

extra holidays - extra parental leave
Remote: 
Full Remote
Contract: 
Full time
Experience: 
Senior (5-10 years)
Work from: 
Philippines, Colombia

Offer summary

Qualifications:

Strong understanding of ML project lifecycle, Experience in NLP, CV, or other ML areas, Ability to productionize ML models, Practical experience with cloud MLOps frameworks, Proven management and leadership skills.

Key responsabilities:

  • Build and mentor effective ML teams
  • Share and contribute best practices
  • Evaluate and improve team knowledge and processes
  • Collaborate with managers on company goals
  • Conduct performance reviews and onboarding
Provectus logo
Provectus Information Technology & Services SME https://www.provectus.com/
501 - 1000 Employees
About Provectus
Provectus is an Artificial Intelligence consultancy and solutions provider, helping businesses achieve their objectives through AI. We are recognized by industry think tanks as a leading provider of AI solutions in specific business domains, driven by sophisticated IT service management and tech innovation. Provectus is a value driver and a trusted partner for our clients and employees. Provectus is an AWS Premier Consulting Partner with competencies in Data & Analytics, DevOps, and Machine Learning. We design and build AI solutions for industry-specific use cases, Data and Machine Learning foundation, Cloud transformation, and DevOps adoption.
See more Provectus offers

Job description

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.

The role of a Practice Leader is the most important for the company’s Machine Learning practice because it is not only about managing people but also requires things to be done. A Practice Leader must have sufficient technical experience to maintain and demonstrate the best market practices while keeping abreast of the latest technologies.

Requirements:
  • We are looking for candidates that combine good software engineering experience for ML applications, and proven people management skills.

    • Technical:
  • Strong understanding of ML project lifecycle.
  • Experience in >1 of the following areas: NLP, CV, forecasting, recommender systems, reinforcement learning.
  • Experience in productionizing of ML models (different modalities).
  • Experience with writing deep learning models from scratch.
  • Ability to make reusable components of ML pipelines.
  • Ability to justify and explain design choices one makes.
  • Practical experience with model post-production & maintenance: model and data monitoring, retraining automation, etc.
  • Practical experience with /AWS/other cloud/open source alternatives/ MLOps platforms, frameworks, and libraries.
  • Strong understanding of Python patterns & best practices.
  • Practical experience with creating training datasets involving human annotators.
  • Practical experience with a variety of data sources (OLTP, OLAP, DataLake, Streaming).
  • Practical experience with Spark, Dask, or similar (distributed data processing).

    • Management:
  • Ability to explain decisions, status, and roadmap to the development team.
  • Ability to explain decisions, status, and roadmap to non-technical customer representatives
  • Experience in team/department leadership.
  • Relationship/team building. Leadership requires building and maintaining a solid and collaborative team of individuals working toward the same goal.
  • Ability to teach and mentor. The role assumes providing employees with their career path and helping them achieve their goals.
  • Diplomatic skills. It means more than just "communication skills" and includes ethics, empathy, compassion, and the ability to resolve conflicts.
  • Calmness. People are complicated, and it is required to be ready for any objectives or misunderstandings.

    • Responsibilities:
  • Build effective teams of ML engineers.
  • Contribute to best practices of the team.
  • Share best practices and culture with the team.
  • Mentor engineers, coach Team Leads, and encourage others to share knowledge.
  • Participate in meetups, and conferences, and build community.
  • Have technical excellence and be an influencer in different teams/projects.
  • Hire and onboard newcomers.
  • Conduct performance reviews and 1-on-1 meetings.
  • Identify and address team gaps in knowledge.
  • Evaluate, improve, and maintain processes.
  • Сollaborate with other managers across the company.
  • Communicate and follow the company's mission, vision, and values.

    • Required profile

    Experience

    Level of experience: Senior (5-10 years)
    Industry :
    Information Technology & Services
    Spoken language(s):
    English
    Check out the description to know which languages are mandatory.

    Hard Skills

    Data ManagementComputer VisionData PipelinesSoftware EngineeringData ProcessingCloud ComputingDask (Software)Machine LearningPython (Programming Language)SparkrReinforcement LearningMLOps (Machine Learning Operations)Deep LearningNatural Language Processing (NLP)Recommender Systems

    Other Skills

    • Calmness Under Pressure
    • Mentorship
    • Team Leadership
    • Verbal Communication Skills
    • Diplomacy
    • Forecasting
    • Relationship Building
    Are you interested?

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