Senior ML OPs Engineer
Senior MLOps Engineer (Applied AI Focus)
Flexible Hybrid Work Model
Location: Remote (hybrid available)
Pay: 198K -230K
*Unfortuantely we are unable to provide sponsorship at this time*
About the Organization
A rapidly growing technology company is building the operating system for creator‑ and content‑driven growth. The team is driven by a mission to make businesses more human and empower individuals to have greater impact. The culture centers around intentionality, collaboration, continuous improvement, and being a genuinely good human in day‑to‑day work.
The organization has been consistently recognized for excellence across workplace culture, innovation, and product leadership. Team members enjoy a flexible work model that blends in‑person collaboration with remote flexibility, encouraging creativity, connection, and individual work‑style preferences.
We are looking for passionate, forward‑thinking builders to join our journey and help shape the future of our industry.
Role Overview
As a Senior MLOps Engineer on the Product Innovations team, you will serve as the technical lead for Applied MLOps. Your work will bridge the gap between experimental research and production‑ready AI systems, with a strong emphasis on ground‑truth generation, model evaluation, and the pre‑/post‑processing infrastructure that powers large‑scale vector embeddings and applied AI features.
You will play a pivotal role in defining best practices, driving evaluation frameworks, and building the infrastructure that enables experimentation and productionization at scale.
What You'll Do
Architect Annotation & Measurement Pipelines
- Design and implement human‑in‑the‑loop and automated annotation workflows.
- Build systems for reliable quality metrics, confidence scoring, and inter‑annotator agreement (IAA).
- Stand up annotation tools and processes to support ground‑truth generation at scale.
Drive Cost‑Efficient Model Evaluation
- Create ground‑truth datasets, golden sets, and model‑by‑model evaluation criteria.
- Benchmark model performance to guide data science decisions and optimize compute and cost efficiency.
- Directly influence product margins by helping deploy the right model for the right use case.
Enforce Applied MLOps Standards
- Implement frameworks for deterministic preprocessing, PII scrubbing, and model‑as‑a‑judge evaluation loops.
- Establish robust production standards for safety, consistency, and reliability.
Collaborate on Model & Product Strategy
- Partner closely with Data Science to drive applied generative AI decisions.
- Influence model selection, architecture, and optimization approaches.
Build & Integrate with Infrastructure
- Work with engineering teams to integrate measurement and evaluation loops into the broader cloud ecosystem (AWS/GCP).
- Ensure automation, observability, and smooth model lifecycle operations.
Who You Are
Annotation & Evaluation Expertise
- Experience building and managing annotation workflows using commercial or custom tools.
- Strong understanding of quality metrics, ground‑truth processes, and IAA methodologies.
Applied MLOps Practitioner
- Hands‑on experience with model monitoring, versioning, evaluation frameworks, and production ML infrastructure.
- Pragmatic and execution‑focused-prioritizing scalable solutions over theoretical perfection.
Technical Proficiency
- Strong Python skills and experience building integrations, pipelines, and tooling for ML systems.
- Understanding of performance trade‑offs between model size, cost, latency, and accuracy.
Cloud & Infrastructure Fluency
- Experience working within cloud ML environments (AWS, GCP, or equivalent).
- Ability to collaborate effectively with DevOps/SRE teams.
Collaborative Technical Leader
- Comfortable acting as a force multiplier for data science teams.
- Strong communication skills and a cross‑functional mindset.
Note: Confidence gaps shouldn't hold you back. If you meet about half of the requirements and feel excited about the work, we encourage you to apply.
What You'll Receive
People & Culture
- Work with talented, collaborative colleagues who are passionate about their craft.
Professional Development
- Access to internal learning platforms, onboarding support, and ongoing training resources.
Lifestyle Benefits
- Meal stipends for remote work days.
- Generous paid time off including vacations, holidays, wellness time, and parental leave.
Health & Financial Benefits
- Comprehensive health coverage (medical, dental, vision, life, disability).
- Retirement savings plan options.
Work‑From‑Home Support
- Stipend to set up a comfortable and productive home office environment.
FAQs
Congratulations, we understand that taking the time to apply is a big step. When you apply, your details go directly to the consultant who is sourcing talent. Due to demand, we may not get back to all applicants that have applied. However, we always keep your CV and details on file so when we see similar roles or see skillsets that drive growth in organisations, we will always reach out to discuss opportunities.
Yes. Even if this role isn’t a perfect match, applying allows us to understand your expertise and ambitions, ensuring you're on our radar for the right opportunity when it arises.
We also work in several ways, firstly we advertise our roles available on our site, however, often due to confidentiality we may not post all. We also work with clients who are more focused on skills and understanding what is required to future-proof their business.
That's why we recommend registering your CV so you can be considered for roles that have yet to be created.
Yes, we help with CV and interview preparation. From customised support on how to optimise your CV to interview preparation and compensation negotiations, we advocate for you throughout your next career move.