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Senior ML Ops Engineer

NYC Office · New York, United States

Pay
Pay not listedSimilar roles state $165K–$240K
Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Product & Technology › ML/AI — team source
Department: Product & Technology › ML/AI
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Do you require visa sponsorship to work legally in the United States (now or in the future)? This includes needing sponsorship for CPT, OPT or other visa types to work in the US.
From the employer’s application form
Apply at Confido

What you’ll work on

Full posting
  • Own ML pipelines from experimentation to production, including training and inference infrastructure

  • Build reproducible environments and fast paths so the AI/ML team can ship new models and agents

  • Set up cloud infrastructure as code and CI/CD for shipping ML safely

  • Serve and optimize inference and forecasting for latency, throughput and cost

  • Keep model and agent quality measurable in production through online evals and human review

From the employer’s posting
Own ML pipelines end to end — experimentation to production — and the infrastructure behind training, inference, and agentic workloads
Give the AI/ML team a paved road: reproducible environments and fast paths from prototype to production
Stand up the cloud foundation as Infrastructure as Code and the CI/CD that ships ML safely
Serve and optimize inference and forecasting workloads — latency, throughput, and cost
keep model and agent quality measurable in production through online evals and human-in-the-loop review

Tools in this posting

  • Java
  • Python
  • Ruby
  • AWS
  • Kafka
  • Kubernetes
  • MLflow
  • Redis
  • SageMaker
  • Snowflake
  • Terraform
  • Airflow
Source — Tool mentions in context
- Deep cloud infrastructure understanding, distributed data systems, and IaC — you can boot an environment from scratch, wire CI/CD, and run containerized workloads in production without hand-holding - Strong Python and comfort in a production app codebase (Ruby, Java) monitoring, security, and cost are instincts, not afterthoughts - High ownership in a fast-moving startup, and experience productionizing what research/AI teams build
- Multimodal or generative AI in production Our stack: Python · Ruby/Rails · AWS · Terraform · Kubernetes · GitHub Actions · Snowflake · Aurora/RDS · Redis · Kafka — with more of the above added as we scale. Learn more about AI @ Confido here
- ML platform and orchestration tooling (MLflow, BentoML, Ray, Airflow) - Large-scale data systems (Snowflake, Kafka) and vector databases - Managed ML services (Bedrock, SageMaker, Vertex AI)
- Inference optimization (vLLM, ONNX, TensorRT) and GPU / spot-instance economics - ML platform and orchestration tooling (MLflow, BentoML, Ray, Airflow) - Large-scale data systems (Snowflake, Kafka) and vector databases
- Large-scale data systems (Snowflake, Kafka) and vector databases - Managed ML services (Bedrock, SageMaker, Vertex AI) - Multimodal or generative AI in production

Posting record

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Open 3 monthsWe first saw this posting 115 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 7, 2026 · 115 days ago
Recorded sightings
69
Last seen by us
Oct 30, 2026

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Job description

View original posting ↗

The brands on your kitchen shelf are run by people doing extraordinary work that nobody sees.

We're building the platform they run on, and a brand they'll be proud to be part of.

Confido is the AI operating system that runs cash application, deductions, trade and planning in one place for CPG brands. That means Finance, Sales, and Ops finally work on the same number.

We’re trusted by 250+ brands managing $30B+ in revenue, including Daisy, OLIPOP, Simple Mills, Idahoan, and more. We've achieved best-in-class growth and recently raised a $55M Series B led by Insight Partners to accelerate our momentum.

If you want your work on shelves everywhere — and outsized ownership while you build — we'd love to meet you.

The Role

Be the first dedicated owner of Confido's ML platform. Our AI/ML team already ships document-understanding, forecasting, and agentic systems into production — on infrastructure we've stood up by hand. You'll own that layer: the pipelines, serving, and cloud foundation that turn models and agents into reliable, cost-efficient production systems, at the scale of hundreds of thousands of documents and heavy LLM/VLM workloads.

Location: New York, NY (Relocation supported)


What you'll do

  • Own ML pipelines end to end — experimentation to production — and the infrastructure behind training, inference, and agentic workloads

  • Give the AI/ML team a paved road: reproducible environments and fast paths from prototype to production, so they can try new models and agents without fighting the infra

  • Stand up the cloud foundation as Infrastructure as Code and the CI/CD that ships ML safely

  • Serve and optimize inference and forecasting workloads — latency, throughput, and cost — and the data streams feeding them (e.g. turning a heavy synchronous model call into an async, parallelized one)

  • Own the data interface with data engineering: serve the right data to models and agents, and write their outputs back into the platform's data systems for the rest of Confido to use

  • Make reliability, observability, security, and privacy the default — and keep model and agent quality measurable in production through online evals and human-in-the-loop review, not just uptime


What we're looking for


Required

  • 5+ years in MLOps, ML platform, AI infrastructure, or platform engineering — on production ML systems, not pipelines on paper

  • You live at the seam of software and infrastructure: equally at home writing production code and standing up cloud infra.

  • You've driven a real pipeline end to end and can walk through it: the architecture, the security and cost trade-offs, and what you'd change

  • Deep cloud infrastructure understanding, distributed data systems, and IaC — you can boot an environment from scratch, wire CI/CD, and run containerized workloads in production without hand-holding

  • Strong Python and comfort in a production app codebase (Ruby, Java) monitoring, security, and cost are instincts, not afterthoughts

  • High ownership in a fast-moving startup, and experience productionizing what research/AI teams build

Nice to have

  • LLMOps tooling — tracing, prompt/version management, eval harnesses

  • Inference optimization (vLLM, ONNX, TensorRT) and GPU / spot-instance economics

  • ML platform and orchestration tooling (MLflow, BentoML, Ray, Airflow)

  • Large-scale data systems (Snowflake, Kafka) and vector databases

  • Managed ML services (Bedrock, SageMaker, Vertex AI)

  • Multimodal or generative AI in production

Our stack: Python · Ruby/Rails · AWS · Terraform · Kubernetes · GitHub Actions · Snowflake · Aurora/RDS · Redis · Kafka — with more of the above added as we scale.

Learn more about AI @ Confido here


🌴 Perks + Benefits

  • Equity — own a meaningful piece of the company you’re helping build

  • Fully paid health coverage through Aetna — we cover 100% of employee premiums

  • Top-tier dental and vision coverage through Guardian

  • Carrot Fertility Pro — comprehensive fertility and family-forming support

  • 12 weeks of paid parental leave

  • Unlimited PTO — plus regular 4-day holiday weekends we actually take

  • 401(k) through Vestwell

  • Paid relocation support — we’ll help you make the move to NYC

  • Fully equipped workspace from day one — laptop, monitor, keyboard, and a $200 stipend to personalize your setup

  • Team perks — catered Friday lunches, team dinners, and unlimited coffee + snacks featuring products from the brands we work with

Confido provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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New York, United States

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