Senior MLOps Engineer
Truecaller is hiring a Senior MLOps Engineer. Level rates it ; you can apply on Truecaller.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Vertex AI and MLOps.
- Level classifies it as a senior role.
- Level lists 34 other open roles at Truecaller.
- The role was posted in the last few days.
AI in this role
Join Truecaller – The place where innovation meets impact!
Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out:
- We are trusted by over 500 million active users every month across 190+ countries
- We identify over 15 billion calls daily, helping users avoid spam and scams
- We are powered by a team of 400+ employees from 45+ nationalities
We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in.
The role:
You'll sit in the Data Infrastructure team, which runs the GCP data and ML platform for the whole company. Vertical teams own their models and use-case logic; you own the platform they build on: training, serving, pipelines, and the tooling around them. This is a role covering company-wide ML infra, so you'll be the go-to person from day one.
What you'll do:
- ML platform on GCP: Vertex AI, Kubeflow Pipelines and GKE-based training and serving infrastructure, kept reliable, secure and cost-efficient.
- Paved roads for ML teams: templates, CI/CD and self-serve tooling so data scientists ship models without filing tickets.
- Model lifecycle: registry, versioning, deployment, rollback, and monitoring for drift and serving health.
- Data integration: feature and training data flows across BigQuery and Airflow together with the data platform engineers.
- Infrastructure as code: everything managed through GitOps with Config Sync, with access following least privilege for PII and policy-tagged data.
- Cost and capacity: GPU/compute usage, quotas, and spend visibility per team.
What you bring in:
- 5+ years in MLOps, ML platform, or platform engineering, with at least 2 years owning production ML infrastructure end-to-end.
- Hands-on GCP: Vertex AI, GKE, and BigQuery in production, not only as skill tags.
- Kubernetes depth: you've run and debugged clusters yourself, not just deployed to them.
- Pipeline orchestration with Kubeflow Pipelines or Vertex AI Pipelines, plus Airflow.
- GitOps for infrastructure (Config Sync or similar) and CI/CD for model deployment.
- Python to production standard, including tests and packaging.
- Proven platform thinking: you've built tooling other teams self-serve on, with docs and SLOs.
- Comfortable working independently as the single owner of a company-wide platform.
It would be great if you also have:
- Streaming features or online inference with Dataflow/Flink and Kafka.
- Feature stores (Vertex AI Feature Store, Feast) and model monitoring tooling.
- LLM serving and evaluation on Vertex AI or similar.
- GPU scheduling and cost optimisation on GKE.
- Experience with data governance (DataHub, policy tags) and privacy regulations such as GDPR or DPDP.
- Prior experience in high-scale consumer products.
What we offer:
We support growth through learning resources, leadership programs, mentoring, and real hands-on work. People can move between teams and projects to build new skills and keep things interesting. We offer clear internal mobility and a transparent path for progression, with leaders who stay involved and provide guidance throughout the year. In addition, you will benefit from:
- A comprehensive compensation package: We offer a competitive salary, 30 days of paid vacation, private health insurance, parental leave top-up, pension, and wellness contributions.
- Modern tools to do your best work: Choose your preferred computer and phone within our budget, so you can work comfortably and efficiently.
- A people-focused office culture: We value in-person collaboration and follow an office-first model, with some flexibility. Our offices offer a vibrant environment with opportunities to learn, connect, and recharge, from breakfast, lunch, and well-stocked snack stations and quiet spaces to team activities such as movie nights, tech meetups, and cultural events. There's something for everyone.
- Truecaller’s “Lab Days” offer a space for imagination: 5 times per year for 3 days, where everyone steps away from their normal tasks to explore new, bold ideas and build things they’ve always wanted to. It’s a space where curiosity leads the way, and prototypes take shape. Some concepts even make it into production, and a few have grown into real features used by millions today. Lab Days allow you to be creative, learn fast, and help shape Truecaller's future.
Come as you are:
Truecaller is committed to building a diverse and inclusive team. We believe that a wide range of backgrounds, perspectives, and experiences strengthens our products and our culture. No matter where you're from, what language you speak, or how you identify, we value what makes you unique and would love to get to know you.
Check out Life at Truecaller - Behind the code: https://www.instagram.com/lifeattruecaller/
Sounds like a great opportunity?
We will fill the position as soon as we find the right candidate, so please send your application as soon as possible. As part of the recruitment process, we will conduct a background check.
We only accept applications in English
How we rate this
Senior MLOps Engineer at Truecaller rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used Vertex AI in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: ML Ops and Vertex AI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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