What are the responsibilities and job description for the Machine Learning Engineer position at Kforce Technology Staffing?
Job Details
RESPONSIBILITIES:
Kforce's client in New York City is looking for a Machine Learning Engineer to join their team!
Responsibilities and Impact:
* Lead ML Engineering to architect, build and deploy production grade GenAI services and solutions
* Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more
* Lead MLOps/LLMOps platform development & automated pipelines focusing on deploying, monitoring and maintaining models in production environments; with model governance, cost and performance optimization
* Collaborate with cross-functional teams to integrate machine learning models into production systems
* Create and manage Documentation and knowledge base, including development best practices, MLOps/LLMOps processes and procedures
* Work closely with members of technology teams in the development, and implementation of Enterprise AI platform
REQUIREMENTS:
* Bachelor's degree in Computer Science, Engineering, or a related field
* 8 years of progressive experience as in machine learning, data analytics or similar roles
5 years of relevant experience with:
* Writing production level, scalable code with Python (or scala)
* MLOps/LLMOps, machine learning engineering, Big Data, or a related role
* Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow
* Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools
* Distributed systems programming, AI/ML solutions architecture, Microservices architecture experience
Additional Preferred Qualifications:
* 2-3 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions
* Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions
* 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases
* Experience with SageMaker and/or Vertex AI
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
Kforce's client in New York City is looking for a Machine Learning Engineer to join their team!
Responsibilities and Impact:
* Lead ML Engineering to architect, build and deploy production grade GenAI services and solutions
* Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more
* Lead MLOps/LLMOps platform development & automated pipelines focusing on deploying, monitoring and maintaining models in production environments; with model governance, cost and performance optimization
* Collaborate with cross-functional teams to integrate machine learning models into production systems
* Create and manage Documentation and knowledge base, including development best practices, MLOps/LLMOps processes and procedures
* Work closely with members of technology teams in the development, and implementation of Enterprise AI platform
REQUIREMENTS:
* Bachelor's degree in Computer Science, Engineering, or a related field
* 8 years of progressive experience as in machine learning, data analytics or similar roles
5 years of relevant experience with:
* Writing production level, scalable code with Python (or scala)
* MLOps/LLMOps, machine learning engineering, Big Data, or a related role
* Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow
* Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools
* Distributed systems programming, AI/ML solutions architecture, Microservices architecture experience
Additional Preferred Qualifications:
* 2-3 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions
* Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions
* 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases
* Experience with SageMaker and/or Vertex AI
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
