Senior MLOps Engineer
Later
Senior MLOps Engineer
Later
Social media management and influencer marketing
Later is the world’s most intelligent influencer marketing company, built to give brands the confidence to create unforgettable campaigns. By combining real creator relationships, trusted intelligence, and expert guidance, Later removes fear and guesswork from one of marketing’s most visible investments.
Built on a native, AI-powered platform and more than a decade of proprietary data—including billions of social interactions, impressions, and $2.4B+ in verified influencer-driven purchases—Later helps teams understand what will work before they launch.
By combining trusted insight with expert guidance, Later removes guesswork from influencer marketing, enabling brands to choose the right creators, execute fully managed campaigns, and drive meaningful growth across awareness, engagement, and revenue. Trusted by leading enterprise brands including Nike, Wayfair, Unilever, and Southwest Airlines, Later bridges creativity and performance so campaigns don’t just look good—they deliver results. Learn more at later.com.
Later is the world’s most intelligent influencer marketing company. Built on a native, AI-powered platform and more than a decade of proprietary data, including billions of social interactions and $2.4B+ in verified influencer-driven purchases, Later helps brands choose the right creators, run fully managed campaigns, and know what will work before they launch.
Trusted by leading enterprise brands including Nike, Wayfair, Unilever, and Southwest Airlines, Later bridges creativity and performance so campaigns don’t just look good, they deliver results. Learn more at later.com.
We’re looking for a Senior MLOps Engineer to build and scale the infrastructure that takes Later’s machine learning and AI systems from prototype to production. You’ll own the pipelines that train, retrain, deploy, and serve the models behind our products, including forecasting, recommendation, and LLM-based and agentic features, across AWS and GCP.
You’ll join the Infrastructure team alongside our DevOps engineers and work closely with Data Science, Data Engineering, Platform, and Product Engineering. Data Science builds and iterates on models; you make sure they ship reliably, scale with demand, and retrain on the right cadence.
At first, expect roughly half your time on ML platform work and half on shared infrastructure. The split will shift toward ML as the practice grows into its own team. The role is mainly infrastructure and automation, with hands-on coding where it counts.
This is a strong fit for a senior engineer with a solid DevOps and cloud foundation and real experience putting ML systems into production, who wants to set the standard for MLOps at Later.
First 30 days: Learn and support.You learn Later’s cloud infrastructure, Kubernetes environments, CI/CD workflows, and the data and ML platform, including how models are trained and deployed today. You start supporting existing pipelines and observability tools. By day 30 you know where the platform’s biggest gaps are and how Product and Data teams use it.
First 60 days: Contribute and improve.You own infrastructure and automation work across Kubernetes, AWS, CI/CD, and the ML platform. You make deployment pipelines more consistent and automated, improve GPU provisioning and monitoring for training and inference, and close gaps in alerting and runbooks. You’re already mentoring teammates on the patterns you’re introducing.
First 90 days: Own and scale.You own the path from a finished model to production. By day 90:
If you don’t meet every requirement but this role sounds like you, we’d still love to hear from you.
We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.
Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only. The salary range listed for this role reflects the zones that applies to the location of this posting.
To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted.
Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.
Salary range:
For candidates located in the US: $125,000-205,000 USD
For candidates located in the Canada: $110,000-160,000 CAD
We have offices in Boston, MA; Vancouver, BC; and Vancouver, WA. For select positions, we are open to hiring fully remote candidates. We post our positions in the location(s) where we are open to having the successful candidate be located.
At Later, we are committed to fostering a culture rooted in an inclusion-first mindset at every level of the company, embracing the importance of hiring and building teams for culture add rather than culture fit. We openly build and maintain unbiased hiring, pay, and promotion practices to create a foundation for an equitable workplace, paving the way for systemic change.
We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All applications will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, national origin, disability, or age. Please let us know if you require any accommodations or support during the recruitment process.
Later provides a suite of social media tools for marketers, brands, and influencers, including social media management, influencer campaign automation, and a multi-destination bio link. Its products work together: Later Social Media Management plans and analyzes posts; Later Influence automates influencer outreach and tracks real-time ROI; Later Link in Bio routes traffic from a single profile link to multiple destinations, all via subscription plans. By combining these tools in one platform and offering expert services for large brands, Later differentiates itself from single-solution competitors and aims to deliver measurable returns from social activity. The company's goal is to help marketers generate predictable, data-driven results from social media and build the first Social Revenue platform.
Explore more opportunities at Later