Senior Software Engineer – ML, Contractor

Janea Systems

Senior ML Engineer contractor taking ML and LLM systems into production for Fortune 500 clients. Building pipelines, MLOps platforms, and RAG systems within Janea’s consulting teams.

Posted 8/5/2026contractRemote • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in deploying ML systems into production, with strong capabilities in Python, MLOps, and LLM systems. Proficient in designing data pipelines and conducting technical audits while effectively communicating technical concepts to non-specialist stakeholders.

Highest-signal resume keywords

ML Systems DeploymentPython ProgrammingMLOps ExpertiseLLM Systems DevelopmentCloud Platforms (AWS, Azure, GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningMLOpsData Pipeline EngineeringPythonPyTorchTensorFlowCI/CDTestingBenchmarkingMonitoring

Soft Skills

Client-Facing CommunicationProblem-Solving

Tools & Technologies

KubernetesAirflowKubeflowArgoDagsterPrefect

Industry Keywords

Enterprise ML SystemsTechnical AuditsCost ControlRetrieval QualityWorkflow Orchestration

Tech Stack

Tools & technologies

AirflowAWSAzureCloudGoogle Cloud PlatformKubernetesPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Take ML or LLM proofs of concept to production with enterprise reliability and cost characteristics
Design and harden data and training pipelines for enterprise ML systems
Perform ML platform and MLOps work, including deployment, versioning, monitoring, evaluation, and model CI/CD
Build LLM and RAG systems, including retrieval quality, evaluation, and cost control
Fill deep technical gaps in client engineering teams for defined periods
Conduct short technical audits and advisory work on existing ML stacks
Work as part of a Janea team on client projects in a client-facing capacity

Requirements

What you’ll need

6+ years of software engineering experience, including 3+ years shipping ML systems into production
Strong Python skills at production code quality
Deep expertise in at least one of LLM and agent systems, ML platform and MLOps, or ML data and pipeline engineering; working competence in the other two
PyTorch or TensorFlow experience and the surrounding production stack
Containers and Kubernetes in at least one major cloud: AWS, Azure, or GCP
Experience with workflow orchestration tools such as Airflow, Kubeflow, Argo, Dagster, or Prefect
Testing, benchmarking, CI/CD, and monitoring practices applied to ML systems
Ability to turn ambiguous business problems into technical plans without close supervision
Client-facing English and ability to explain technical trade-offs to non-ML-specialist stakeholders
Own equipment
Legal entity for invoicing
Typically 40 hours per week unless specified differently
Minimum four hours of daily overlap with US business hours for most engagements
Independent contractor basis, invoicing through own company or registered sole-trader entity

Benefits

Comp & perks

Substantive work on Fortune 500 engineering problems and core systems
Work alongside Janea’s senior engineers
Short chain of command and minimal process overhead
Rate, scope, and invoicing terms agreed in writing before starting
Repeat work and first look at the next relevant project for contractors who deliver
No unpaid work
Relevant projects presented before going to market