Machine Learning Ops Engineer
Data Practice /
The Patrick J. McGovern Foundation (PJMF) is a private foundation dedicated to advancing artificial intelligence and data science solutions to create a thriving, equitable, and sustainable future for all. PJMF works in partnership with public, private and social institutions to drive progress on our most pressing challenges, including digital health, climate change, broad digital access, and data maturity in the social sector.
For more information, please visit our website at https://www.mcgovern.org/. Core to PJMF’s mission is inclusion, diversity, equity, and accessibility (IDEA). We apply the IDEA framework to all we do, from growing a diverse team within the foundation to coalition building with organizations and people around the world, and to democratizing the development and rewards of AI and data.
About the Role:
PJMF’s Data Practice team connects nonprofit organizations worldwide with expert technical guidance and practical hands-on experience using advanced data approaches and tools that can simultaneously move a nonprofit forward on its data journey while unlocking new pathways to impact. The team’s approach is issue-, tech-, and region-agnostic, creating an open space for nonprofits to explore the data solutions best suited to their work, communities, and contexts – rather than limiting choices to the data solutions most accessible to them in the near term.
PJMF’s Data Practice seeks a civic-minded, socially-conscious, and industry-experienced MLOps Engineer to join its team of technical leads and program implementation specialists in supporting nonprofit grant partners as they progress their respective data journeys. Data Practice grant partnerships are high-touch engagements between nonprofit staff with varying levels of data expertise and experienced PJMF data practitioners with industry-level skill sets. Over the course of each calendar year, Data Practice operations run on two tracks: implementation of Data Practice programs with grant partners selected in the previous calendar year, and strategy development and selection of grant and implementation partners for the next calendar year. Data Practice technical and program staff collaborate closely to both select Data Practice partners and implement Data Practice programs.
In this role, you will join the team’s Data Scientist, Cloud Engineer, and Data Engineer as a Data Practice technical lead, providing a combination of ML/DevOps instruction, mentorship, and guidance to nonprofits seeking to explore the value of integrating advanced data tools and approaches into their work. The Data Practice’s MLOps Engineer will be expected to serve as a trusted advisor to individual grant partners, with a willingness to both troubleshoot acute data challenges and engage in the co-creation of solutions designed for longer-term impact.
Relationship management, facilitated by both technical leads and program implementation specialists on the Data Practice team, is critical to creating the trusted environment required to enable and document learning between the Foundation and its grant partners, and among the grant partners themselves. We seek candidates with sharp communication skills, patience, discretion, awareness of the contexts and constraints commonly experienced by nonprofits, and a commitment to knowledge capture and continuous learning. This position will report to the Director, Data Practice.
How you will make an impact:
- Advise grant partners on technology selection, software architecture design, security practices, and implementation, including productionization and scalable deployment of machine learning models and data-enabled applications
- Regularly learn and implement new technologies, and play an active advisory role in developing, proving out, and (re)assessing solutions under exploration by grant partners
- Lead scoping exercises with prospective and current grant partners on stability, application delivery, and availability
- Maintain a strong security awareness through frequent software architecture design reviews
- Keep up-to-date with latest developments in machine learning and DevOps, particularly with regard to cloud services and the use of data technology by nonprofits, and share your knowledge with the Data Practice team and grant partners
- Assist in evaluating the reliability, accuracy, and cost-effectiveness of machine learning models and work with grant partners to identify areas of improvement
- Work with individual nonprofits to connect the gap from development to production for ML and natural language processing (NLP) models under the constraints of scalability, correctness, maintainability, and efficiency
- Develop scripts and processes to optimize and automate ML and NLP models in production within the cloud and bring subject matter expertise about data storage and object-oriented programing
- Develop strategies to track model performance and drift, identifying models that need to be retrained
What you will need to succeed:
- "Data for Good". Understanding of / interest in the use of responsible AI for international development or social/environmental impact work
- Knowledge and Expertise. MLOps experience automating processes, using data to make better decisions, using software to make processes more efficient, improving the quality of the product or service provided by an organization, and improving speed of delivery
- Strategic Mindset. Systems thinker capable of analyzing and distilling observations, ideas, and feedback into team notes, memos, and slide presentations
- Context Awareness & Spirit of Inquiry. Familiarity with the institutions and networks most relevant to our work. Empathy for the challenges – data or otherwise – nonprofits face in delivering impact. Desire to learn together with and from, rather than preach to, partners.
- Thoughtfulness. Be a thoughtful, responsible representative of the Foundation and remain mindful of power dynamics when interacting with external stakeholders. Proactively identify potential issues or roadblocks in external relationships and follow team norms when addressing them
- Creativity. Ability to see an opportunity beyond the status quo and develop a roadmap to get there
- Adaptability. Entrepreneurial spirit and the ability to transition between independent, project-based, and team-based work with ease from a remote location
- Teamwork. Self-management skills and ability to work as part of a nimble and fast-moving team; strong multitasking and parallel development abilities
- 100% Remote. Desire to work remotely, but not alone - with mature, socially minded professionals
- Work eligibility. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
Tech experience you will need to succeed:
- Extensive knowledge & experience with Git, Linux system administration, Kubernetes/Docker, ML data pipelines, databases (SQL, NoSQL, RDS, CloudSQL, DynamoDB, Redshift, etc.), cloud services (at least AWS and/or GCP), and distributed systems
- Ability to code in multiple languages (Python and SQL; R, Java, or others as well)
- Strong communication and problem-solving skills with the ability to discuss projects with colleagues who have limited knowledge of ML/DevOps techniques and tools
- Ability to oversee and provide input regarding infrastructure design and maintenance
What we offer:
- Competitive Salary – Anticipated starting salary of $108,000 - $145,000 with flexibility based on experience
- Health Coverage – Foundation-paid medical, dental, and vision insurance for employees, spouses/domestic partners, and dependents. HSA/FSA plans, life insurance, and short- and long-term disability coverage
- Long-term Rewards – 401(k) retirement plan with generous matching up to 6% of annual pay, plus an additional discretionary match at the end of year
- Flexible PTO – Unlimited paid time off, which allows team members to take the time they need for vacation or illness so they can return to work able to contribute fully to our mission. The foundation recognizes 11 paid national holidays per year and may also announce closure for local, regional, or state holidays
- Remote Work Environment – Ability to work 100% remotely, but not alone - with mature, socially minded professionals
- Wellness Support – Access to Ginger, Gympass, Headspace, and SmartSpend Plus, along with financial well-being providers
- Parental Leave – Up to 6 months of gender-neutral paid leave for parents and caregivers when they have a new addition to their families
- Learning Reimbursements – Foundation policy encouraging employees to explore development opportunities such as peer learning, internal trainings, and external activities; savings on student loans (available via insurance provider)
- Philanthropic Gift Matching – opportunity for team members to support vulnerable communities, reflecting PJMF’s commitment to social impact
The attributes listed above represent our current thinking for the role. You can be a great candidate even if you don't fit everything we've described below. You can also have important skills we haven't thought of. If that's you - even if you’re on the fence - we encourage you to apply and tell us about yourself!
We have built an environment that celebrates the differences in backgrounds and experiences. PJMF invests in activities that lead to greater inclusion, diversity, equity, and accessibility in how AI and data are conceptualized, developed, applied, and deployed. We are applying the same framework as our team grows and expands. We are an equal opportunity employer and we especially encourage and invite members of traditionally underrepresented communities to apply.
All PJMF team members must be fully vaccinated against COVID-19.