Overview
Remote
On Site
$40 - $50 hourly
Contract - W2
Contract - Temp
Skills
Machine Learning Operations (ML Ops)
Deep Learning
Vertex
Torch
Docker
Kubernetes
Machine Learning (ML)
Data Engineering
SQL
Data Science
Software Engineering
Communication
Python
PyTorch
TensorFlow
Cloud Computing
Google Cloud Platform
Google Cloud
Scratch
Artificial Intelligence
Messaging
Job Details
RESPONSIBILITIES:
Kforce has a client seeking a remote Machine Learning Engineer to join their team.
Summary:
The Machine Learning Engineer will be primarily working on machine learning enablement. The goal is to help them accelerating on their machine learning projects/applications. This team will analyze how users adopt ML and identify the needs, and work with the other teams to strategically plan out how to make machine learning experience better. This is a new team and their long term goal is to continue to build/scale ML apps in the cloud and ultimately support the business and their needs to help drive revenue.
As a Machine Learning Engineer, you will be assisting other teams for MLOps projects to deliver an end-to-end production ready ML model pipeline for deep learning and non-representation-based ml model using Vertex AI, MLFLOW, TensorFlow, Pytorch, Sci-kit learn TensorFlow Serving, Torch Serving, mlflowServing, Docker, Kubernetes and Google Cloud Platform. They will be building their own models for other teams to then use.
REQUIREMENTS:
* Computer Science degree/Masters in ML/AI or equivalent experience
* 2-6+ years of ML and Data Engineering experience
* Proficiency in Python, Pytorch, Tensorflow and Google Cloud Platform
* Experience with VertexAI
* Strong in SQL
* Understands data science from hypothesis to production
* Overall strong software engineering background
* Strong communication and culture fit (outgoing, team player, extremely collaborative)
* Proficient in Python/Pytorch (and other libraries) tensorflow, Cloud (Google Cloud Platform a plus), along with several other languages and technologies
* Experience building at least 2+ models on their own from scratch
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 has a client seeking a remote Machine Learning Engineer to join their team.
Summary:
The Machine Learning Engineer will be primarily working on machine learning enablement. The goal is to help them accelerating on their machine learning projects/applications. This team will analyze how users adopt ML and identify the needs, and work with the other teams to strategically plan out how to make machine learning experience better. This is a new team and their long term goal is to continue to build/scale ML apps in the cloud and ultimately support the business and their needs to help drive revenue.
As a Machine Learning Engineer, you will be assisting other teams for MLOps projects to deliver an end-to-end production ready ML model pipeline for deep learning and non-representation-based ml model using Vertex AI, MLFLOW, TensorFlow, Pytorch, Sci-kit learn TensorFlow Serving, Torch Serving, mlflowServing, Docker, Kubernetes and Google Cloud Platform. They will be building their own models for other teams to then use.
REQUIREMENTS:
* Computer Science degree/Masters in ML/AI or equivalent experience
* 2-6+ years of ML and Data Engineering experience
* Proficiency in Python, Pytorch, Tensorflow and Google Cloud Platform
* Experience with VertexAI
* Strong in SQL
* Understands data science from hypothesis to production
* Overall strong software engineering background
* Strong communication and culture fit (outgoing, team player, extremely collaborative)
* Proficient in Python/Pytorch (and other libraries) tensorflow, Cloud (Google Cloud Platform a plus), along with several other languages and technologies
* Experience building at least 2+ models on their own from scratch
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.