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HomeCompaniesC The SignsSenior MLOps Engineer

Senior MLOps Engineer

C The Signs · United States (Remote) · Remote · Active · Workable

Job facts

FieldValue
CompanyC The Signs
TitleSenior MLOps Engineer
Normalized title-
Department / teamOther
LocationUnited States
Work modelRemote / Remote
Employment typeFull Time
Salary-
Statusactive
ATS providerWorkable
Posted / first seen2026-03-04 / 2026-05-31
Changed / last seen2026-05-31 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from C The Signs.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Workable.Open
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Department jobsActive postings in Other.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyC The Signs
Sourcec0cdce61-3e3d-481f-ac34-799da9c624b4
ATS providerWorkable

Description

Description Position Summary We’re hiring a Senior MLOps Engineer with deep machine learning engineering experience to build and operate the production platform powering ML/LLM driven healthcare workflows. You’ll design reliable, secure, and compliant systems for model development, evaluation, deployment, monitoring, and continuous improvement—working closely with ML, data, security, and product teams. This role is ideal for someone who has shipped ML systems in production and is excited about LLM orchestration, RAG, evaluations, guardrails, and observability in a regulated environment. Key responsibilities MLOps & ML Platform Design and operate ML platforms that support end to end workflows: data ingestion, feature engineering, training, evaluation, deployment, and monitoring. Build and maintain CI/CD for ML (testing, packaging, versioning, reproducibility, automated rollbacks, approvals). Implement MLOps best practices: model registry, experiment tracking, lineage, governance, and reproducible training environments. Develop scalable training infrastructure (distributed training, GPU scheduling, cost controls, auto scaling). Create and maintain feature pipelines / feature stores, ensuring consistency between training and inference (training serving skew prevention). Establish model monitoring and observability: performance, drift, bias/fairness signals (where relevant), latency, throughput, and data quality. Build and own end to end LLM delivery pipelines: prompt/versioning, retrieval, orchestration, evaluation, deployment, monitoring, and iterative improvement. Create robust LLM evaluation harnesses (offline + online): golden datasets, automated regression testing, human in the loop review workflows, and risk scoring. Build cost controls: token/cost budgeting, caching strategies, autoscaling, and performance tuning. Deployment, reliability, and operations Productionize ML Models on GCP using containers and orchestration (e.g., GKE, Cloud Run), and build CI/CD for ML/LLM systems with automated tests and safe rollouts. Implement observability: tracing, metrics, logs, dashboards, alerting for model/system health (latency, token usage, error rates, retrieval quality, hallucination indicators, drift where relevant). Build cost controls: token/cost budgeting, caching strategies, autoscaling, and performance tuning. Data, governance, and compliance (Healthcare) Design systems with security and privacy by default: IAM, least privilege, secrets management, audit logs, encryption, data retention, and PHI/PII handling. Implement governance: model/prompt lineage, dataset provenance, evaluation traceability, and approval workflows aligned with healthcare compliance expectations. Integrate guardrails: content filters, policy checks, prompt injection defenses, structured output validation, and fallback strategies. Requirements 6+ years in software/platform engineering, including 4+ years operating ML systems in production (or equivalent depth). Strong experience in ML engineering: training pipelines, evaluation, deployment patterns, monitoring, and iteration loops. Strong engineering skills in Python, plus production grade experience building APIs/services. Demonstrated hands on experience with LLM systems in production and ML engineering: training pipelines, evaluation, deployment patterns, monitoring, and iteration loops. Strong experience with GCP services and cloud native patterns. Experience with Vertex AI (pipelines, endpoints, feature store, model registry, evaluation) and/or managed vector search on GCP. Experience with containerization and orchestration (Docker, Kubernetes/GKE and/or Cloud Run). Benefits Why Join Us? Joining  C the Signs  is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact. Benefits: Competitive salary and benefits package. Flexible working arrangements (remote or hybrid options available). The opportunity to work on life changing AI technology that directly impacts patient outcomes. Join a team that combines cutting edge innovation with a mission to save lives and improve health equity. Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.

Full job record

Job IDa44ecbf8f6fcb0eab8e95f011abb7ee226b2e520
Org ID80a156fe-fe28-40ac-8f76-79f62cd700cf
Source IDc0cdce61-3e3d-481f-ac34-799da9c624b4
Board IDc0cdce61-3e3d-481f-ac34-799da9c624b4
Providerworkable
Provider Job Key070D1EB209
TitleSenior MLOps Engineer
Normalized Title
Statusactive
Activeyes
Location TextUnited States (Remote)
DepartmentOther
Team
Employment Typefull_time
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
City
Salary RawDescription Position Summary We’re hiring a Senior MLOps Engineer with deep machine learning engineering experience to build and operate the production platform powering ML/LLM driven healthcare workflows. You’ll design reliable, secure, and compliant systems for model development, evaluation, deployment, monitoring, and continuous improvement—working closely with ML, data, security, and product teams. This role is ideal for someone who has shipped ML systems in production and is excited about LLM orchestration, RAG, evaluations, guardrails, and observability in a regulated environment. Key responsibilities MLOps & ML Platform Design and operate ML platforms that support end to end workflows: data ingestion, feature engineering, training, evaluation, deployment, and monitoring. Build and maintain CI/CD for ML (testing, packaging, versioning, reproducibility, automated rollbacks, approvals). Implement MLOps best practices: model registry, experiment tracking, lineage, governance, and reproducible training environments. Develop scalable training infrastructure (distributed training, GPU scheduling, cost controls, auto scaling). Create and maintain feature pipelines / feature stores, ensuring consistency between training and inference (training serving skew prevention). Establish model monitoring and observability: performance, drift, bias/fairness signals (where relevant), latency, throughput, and data quality. Build and own end to end LLM delivery pipelines: prompt/versioning, retrieval, orchestration, evaluation, deployment, monitoring, and iterative improvement. Create robust LLM evaluation harnesses (offline + online): golden datasets, automated regression testing, human in the loop review workflows, and risk scoring. Build cost controls: token/cost budgeting, caching strategies, autoscaling, and performance tuning. Deployment, reliability, and operations Productionize ML Models on GCP using containers and orchestration (e.g., GKE, Cloud Run), and build CI/CD for ML/LLM systems with automated tests and safe rollouts. Implement observability: tracing, metrics, logs, dashboards, alerting for model/system health (latency, token usage, error rates, retrieval quality, hallucination indicators, drift where relevant). Build cost controls: token/cost budgeting, caching strategies, autoscaling, and performance tuning. Data, governance, and compliance (Healthcare) Design systems with security and privacy by default: IAM, least privilege, secrets management, audit logs, encryption, data retention, and PHI/PII handling. Implement governance: model/prompt lineage, dataset provenance, evaluation traceability, and approval workflows aligned with healthcare compliance expectations. Integrate guardrails: content filters, policy checks, prompt injection defenses, structured output validation, and fallback strategies. Requirements 6+ years in software/platform engineering, including 4+ years operating ML systems in production (or equivalent depth). Strong experience in ML engineering: training pipelines, evaluation, deployment patterns, monitoring, and iteration loops. Strong engineering skills in Python, plus production grade experience building APIs/services. Demonstrated hands on experience with LLM systems in production and ML engineering: training pipelines, evaluation, deployment patterns, monitoring, and iteration loops. Strong experience with GCP services and cloud native patterns. Experience with Vertex AI (pipelines, endpoints, feature store, model registry, evaluation) and/or managed vector search on GCP. Experience with containerization and orchestration (Docker, Kubernetes/GKE and/or Cloud Run). Benefits Why Join Us? Joining  C the Signs  is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact. Benefits: Competitive salary and benefits package. Flexible working arrangements (remote or hybrid options available). The opportunity to work on life changing AI technology that directly impacts patient outcomes. Join a team that combines cutting edge innovation with a mission to save lives and improve health equity. Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://apply.workable.com/c-the-signs/jobs/view/070D1EB209
Apply URLhttps://apply.workable.com/c-the-signs/j/070D1EB209/apply
First Seen At2026-05-31 17:47:30Z
Last Seen At2026-06-06 13:32:14Z
Last Checked At2026-06-06 13:32:14Z
Last Changed At2026-05-31 17:47:30Z
Inactive At
Source Posted At2026-03-04 00:00:00Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=workable/board=c-the-signs/date=2026-06-06/2026-06-06T13-32-14-201Z-1d7e9089a1f44896e8046ec330c66acb780333ce7f00506c73e19318243ac2e3.json
Event Fields
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Parsed Structured
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Extensions
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Native Structured
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