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Engineering Manager (Machine Learning)

evolutioniq · 30+ days ago
Negotiable
Full-time
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About us: EvolutionIQ’s mission is to improve the lives of injured and disabled workers and enable them to return to the workforce, saving billions of dollars in avoidable costs and lost productivity to the US and global economies and make insurance more affordable for everyone. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. We’re backed by First Round Capital, FirstMark Capital, Foundation Capital, Brewer Lane Ventures, and have been named as Inc.’s top places to work

Your Impact: This Engineering Manager will be responsible for overseeing a team of Machine Learning Engineers that are training and deploying highly scalable ML models. The role requires strong ML technical expertise, leadership skills, and the ability to work collaboratively across Engineering teams, Product, and other functions.

Key Responsibilities:

  • Manage and lead the team, define the strategic direction of our platforms in alignment with the company's overall technology and Product strategy.
  • Maintain a hands-on approach and willingness to stay connected with the code by regularly contributing to the codebase with small fixes and enhancements
  • Collaborate closely with other engineering teams, product managers, and stakeholders to understand their needs, translate them into technical requirements, and support your team’s execution
  • Foster a culture of continuous learning, caring, and improvement within the team and in the broader engineering organization, promoting the adoption of best practices in code quality, testing, and maintainability.
  • Implement and manage robust security protocols to protect our platforms and data.
  • Lead recruitment, mentoring, and professional development initiatives within the team, fostering a culture of excellence and high performance.
  • Continually evaluate emerging technologies and industry trends, assessing their potential application to our organization.

Qualifications:

  • 5-8+ years of experience, with at least 2 years managing a machine learning focused team of 5+ engineers
  • Technical expertise training and deploying highly scalable ML models
  • Strong understanding of data science and statistics
  • Proven track record of successfully translating client business problems into ML problems
  • Proven track record of successfully implementing new technologies within organizations
  • Bachelor's degree in Computer Science or related field preferred

Work-life, Culture & Perks: 

  • Compensation: competitive salary (the range for this role is 220-250K) with flexibility, as well as a meaningful equity plan offered (stock options)
  • Well-Being: Full medical, dental, vision, short- & long-term disability, 401k matching. 100% of the employee contribution up to 3% and 50% of the next 2%
  • Work/Life Balance: For this role we are hoping this person can work out of the NYC office regularly with much of our leadership with flexibility.
  • Home & Family: Flexible PTO, 100% paid parental leave (4 months for primary caregivers and 3 months for secondary caregivers), sick days, paid time off. For new parents returning to work we offer a flexible schedule. We also offer sleep training to help you and your family navigate life schedules with a newborn
  • Office Life: Hybrid schedule, catered lunches, happy hours, and pet-friendly office space. $500 for your in home office setup and $200/year for upgrades every year after your initial setup
  • Growth & Training: $1,000/year for each employee for professional development, as well as upskilling opportunities internally
  • Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active H1-B visa


EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees

Last updated on Aug 22, 2024

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