or apply directly on DeepIntent's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 16 days DeepIntent's roles stay open a median of 40 days
- Reposted
- No
- Salary listed
- No 64% of DeepIntent's roles list one
- Ghost-job risk at DeepIntent
- high 6 stale, 0 reposted of 14 open
- Hiring momentum
- 20 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 DeepIntent's own greenhouse board since 2026-08-03. Full hiring picture for DeepIntent.
About this role
As an MLOps Engineer at DeepIntent, you will work closely with Data Science and AI teams to build and scale a high-performance machine learning platform. Your responsibilities will include implementing MLOps best practices, maintaining model tracking and observability, and designing deployment infrastructure for ML/AI systems. You will also manage project priorities and collaborate on ML/AI-driven feature development.
- benefits
- 4/5
- freshness
- 4/5
- career value
- 4/5
- role clarity
- 4/5
- 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 DeepIntent as an employer.
What you need
- Bachelor's degree in Computer Science or similar technical field of study, or equivalent practical experience
- Strong software engineering skills in complex, distributed, multi-language systems (Python preferred)
- Hands-on experience with Spark, Docker and Kubernetes in production environments
- Experience building and operating end-to-end distributed systems
- Experience developing and maintaining ML systems built with open-source MLOps tools (e.g., MLflow, Argo, Metaflow, Airflow, Kubeflow)
- Strong understanding of software testing, benchmarking, and CI/CD practices
Nice to have
- Familiarity with LLM/generative AI tooling and concepts (model serving frameworks, embeddings, vector stores, RAG pipelines)
- Familiarity with GPU infrastructure - CUDA fundamentals, GPU scheduling/orchestration in Kubernetes, and driver/toolkit management (NVIDIA drivers, CUDA toolkit, cuDNN)
What you get
- Competitive base salary plus performance-based bonus
- Comprehensive medical insurance
- Flexible PTO
- Hybrid-friendly culture with flexible work options
- Professional development reimbursement
- WiFi reimbursement
Worth weighing
- No specific salary listed
- Focus on MLOps and AI infrastructure may limit exposure to other areas of software engineering
- The role requires collaboration with data scientists, which may require strong interpersonal skills
Summarised from DeepIntent's posting. Read the full original.
Listed by DeepIntent on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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