Confido

2 weeks ago

Senior ML Ops Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Own the first dedicated ML platform within the AI/ML team, taking models and agents from experimentation to reliable, cost-efficient production. Build and maintain end-to-end ML pipelines, cloud infrastructure as code, and CI/CD for safe deployment. Serve and optimize inference and forecasting workloads for latency, throughput, and cost, while partnering with data engineering on the data interfaces. Drive reliability, observability, security, privacy, and production quality through online evals and human-in-the-loop review.

Location: New York

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Own ML pipelines end to end, from experimentation to production, including training, inference, and agentic workloads.
•Create reproducible environments and reliable pathways from prototype to production to reduce infra friction for the AI/ML team.
•Stand up cloud foundation using Infrastructure as Code and implement CI/CD that ships ML safely.
•Serve and optimize inference and forecasting workloads, improving latency, throughput, and cost, including async/parallelized execution where needed.
•Partner with data engineering to serve the right data to models and write model outputs back into Confido’s platform data systems while ensuring reliability, observability, security, privacy, and measurable quality via online evals and human-in-the-loop.

Pay and Benefits

Schedule:4-Day Week

Perks:EquityHealth InsuranceDentalVisionParental LeavePaid Leave401kRelocationStipend

Key Requirements

•5+ years in MLOps, ML platform, AI infrastructure, or platform engineering, focused on production ML systems.
•Comfort living at the seam of software and infrastructure—writing production code and standing up cloud infrastructure.
•Own an end-to-end ML pipeline and explain architecture, security, cost trade-offs, and improvements you’d make.
•Deep understanding of cloud infrastructure, distributed data systems, and IaC, including CI/CD and running containerized workloads in production.
•Strong Python and comfort in a production app codebase, with monitoring, security, and cost as instincts.

Experience:5+ yearsMLOpsAI infrastructureML platformProduction ML systems

Skills:High ownershipProductionizing AIReliability focusSecurity mindsetCost awareness

Tech Stack:PythonRubyRailsAWSTerraformKubernetesGitHub ActionsSnowflakeAuroraRDSRedisKafkaInfrastructure as CodeCI/CDLLMOps toolingVLLMONNXTensorRTMLflowBentoML

Eligibility

Nationality:US National

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Confido

Provides custom software development, cloud solutions, and IT consulting services to help businesses build scalable web and mobile applications, implement cloud infrastructure, and improve security and operational efficiency through tailored technology solutions.

Industry: Professional Services

Website

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Confido

2 weeks ago

Senior ML Ops Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: New York

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Own ML pipelines end to end, from experimentation to production, including training, inference, and agentic workloads.
•Create reproducible environments and reliable pathways from prototype to production to reduce infra friction for the AI/ML team.
•Stand up cloud foundation using Infrastructure as Code and implement CI/CD that ships ML safely.
•Serve and optimize inference and forecasting workloads, improving latency, throughput, and cost, including async/parallelized execution where needed.
•Partner with data engineering to serve the right data to models and write model outputs back into Confido’s platform data systems while ensuring reliability, observability, security, privacy, and measurable quality via online evals and human-in-the-loop.

Pay and Benefits

Schedule:4-Day Week

Perks:EquityHealth InsuranceDentalVisionParental LeavePaid Leave401kRelocationStipend

Key Requirements

•5+ years in MLOps, ML platform, AI infrastructure, or platform engineering, focused on production ML systems.
•Comfort living at the seam of software and infrastructure—writing production code and standing up cloud infrastructure.
•Own an end-to-end ML pipeline and explain architecture, security, cost trade-offs, and improvements you’d make.
•Deep understanding of cloud infrastructure, distributed data systems, and IaC, including CI/CD and running containerized workloads in production.
•Strong Python and comfort in a production app codebase, with monitoring, security, and cost as instincts.

Experience:5+ yearsMLOpsAI infrastructureML platformProduction ML systems

Skills:High ownershipProductionizing AIReliability focusSecurity mindsetCost awareness

Tech Stack:PythonRubyRailsAWSTerraformKubernetesGitHub ActionsSnowflakeAuroraRDSRedisKafkaInfrastructure as CodeCI/CDLLMOps toolingVLLMONNXTensorRTMLflowBentoML

Eligibility

Nationality:US National

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Confido

Industry: Professional Services

Website