or apply directly on Attain's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 14 days Attain's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 0% of Attain's roles list one
- Ghost-job risk at Attain
- high 11 stale, 0 reposted of 16 open
- Hiring momentum
- 18 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Attain's own greenhouse board since 2026-08-03. Full hiring picture for Attain.
About this role
As a Senior Machine Learning Engineer at Klover, you will be responsible for owning and operating production ML systems and building the MLOps infrastructure for their B2C financial services. Your day-to-day tasks include designing and maintaining pipelines, model-serving infrastructure, and automating the ML lifecycle to ensure reliability and performance. You will collaborate with data scientists and other teams to streamline model deployment and improve product velocity.
- benefits
- 1/5
- freshness
- 4/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Attain as an employer.
What you need
- 5+ years of direct experience as a Machine Learning Engineer, ML Platform Engineer, MLOps Engineer, Applied Scientist or similar role building and operating production ML systems
- Strong expertise deploying, serving, monitoring, and operating ML models in production
- Hands-on MLOps experience: pipelines, CI/CD for ML, containerization (Docker), orchestration (Kubernetes), infrastructure-as-code (e.g., Terraform)
- Strong Python coding skills
- Strong software and platform engineering fundamentals
Nice to have
- Degree in STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, Operations Research, or a related quantitative field
- Experience building low-latency online model serving
- Experience with model versioning, reproducibility, and safe progressive rollout of models in production
- Familiarity with model explainability, auditability, and compliance considerations of regulated decisioning
- Experience with distributed computing and GPU-accelerated workloads
Worth weighing
- No salary listed
- Role involves significant hands-on infrastructure work
- Hybrid schedule with 4 days in-office and 1 day remote may not suit everyone
Summarised from Attain's posting. Read the full original.
Listed by Attain on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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