ML Pipeline Engineer
Immediate need for a talented Machine Learning Engineer. This is a 12 Months Contract opportunity with long-term potential and is located in Westlake, TX(Hybrid) . Please review the job description below and contact me ASAP if you are interested.
Job Diva ID: 26-04258 Pay Range: $65 - $ 70/hour . Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
Key Responsibilities:
ā¢ Productionize machine learning and GenAI models into scalable, high-availability services
ā¢ Design and implement end-to-end ML pipelines including training, deployment, monitoring, and lifecycle management
ā¢ Build and manage agent-based workflows using modern orchestration frameworks
ā¢ Collaborate with data scientists to operationalize models and support ongoing evaluation and improvement
ā¢ Ensure robust monitoring, logging, and performance tracking for deployed models
ā¢ Apply DevOps and MLOps best practices to support scalable ML deployments
Key Requirements and Technology Experience:
ā¢ Strong experience with agent orchestration frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar
ā¢ Hands-on experience developing, deploying, and supporting statistical and machine learning models in production
ā¢ Proficiency with AWS services including S3, Lambda, ECS, SageMaker, and related cloud infrastructure
ā¢ Experience with CI/CD, DevOps, and MLOps practices
ā¢ Strong software engineering background with a focus on scalable system design
ā¢ Experience managing multiple models in production environments
ā¢ Strong understanding of model monitoring, drift detection, and performance optimization
ā¢ Ability to work cross-functionally with engineering, data science, and platform teams
Candidates should be prepared to discuss: End-to-end ML development, deployment, and production monitoring; Designing scalable architectures for deploying dozens of ML models; Strategies for persisting predictions and ML lifecycle data for evaluation and governance; Diagnosing and responding to model drift; SQL proficiency and best practices when operationalizing data science logic.
Our client is a leading Financial Industry and we are currently interviewing to fill this and other similar contract positions.
OpenKyber 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.
By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails from OpenKyber and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy.
For applications and inquiries, contact: [email protected]
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Job Diva ID: 26-04258 Pay Range: $65 - $ 70/hour . Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
Key Responsibilities:
ā¢ Productionize machine learning and GenAI models into scalable, high-availability services
ā¢ Design and implement end-to-end ML pipelines including training, deployment, monitoring, and lifecycle management
ā¢ Build and manage agent-based workflows using modern orchestration frameworks
ā¢ Collaborate with data scientists to operationalize models and support ongoing evaluation and improvement
ā¢ Ensure robust monitoring, logging, and performance tracking for deployed models
ā¢ Apply DevOps and MLOps best practices to support scalable ML deployments
Key Requirements and Technology Experience:
ā¢ Strong experience with agent orchestration frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar
ā¢ Hands-on experience developing, deploying, and supporting statistical and machine learning models in production
ā¢ Proficiency with AWS services including S3, Lambda, ECS, SageMaker, and related cloud infrastructure
ā¢ Experience with CI/CD, DevOps, and MLOps practices
ā¢ Strong software engineering background with a focus on scalable system design
ā¢ Experience managing multiple models in production environments
ā¢ Strong understanding of model monitoring, drift detection, and performance optimization
ā¢ Ability to work cross-functionally with engineering, data science, and platform teams
Candidates should be prepared to discuss: End-to-end ML development, deployment, and production monitoring; Designing scalable architectures for deploying dozens of ML models; Strategies for persisting predictions and ML lifecycle data for evaluation and governance; Diagnosing and responding to model drift; SQL proficiency and best practices when operationalizing data science logic.
Our client is a leading Financial Industry and we are currently interviewing to fill this and other similar contract positions.
OpenKyber 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.
By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails from OpenKyber and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy.
For applications and inquiries, contact: [email protected]
Apply tot his job
Apply To this Job