Home

Azure Machine Learning Engineer--Dallas, Texas (Onsite) at Dallas, Texas, USA
Email: [email protected]
http://bit.ly/4ey8w48
https://jobs.nvoids.com/job_details.jsp?id=710776&uid=

Passport Number is Mandatory

Hi,

Greetings From Ampstek !!

We are a Global staffing firm and we are Tier 1 vendor for all requirements and we can close positions immediately. 

Please review our job opening below and kindly send us the updated resume ASAP along with the details of consultants;

Please add [email protected]
 in your distribution list

Job Title : Azure ML Engineer

Experience : 10 years 

Location: Dallas, Texas (Onsite) 

Long-Term Contract.

Job Description:

We are seeking an experienced Sr. Developer Machine Learning Engineer
to join our team. The successful candidate will be responsible for building and scaling state-of-the-art recommendation engines leveraging the latest machine learning techniques and technologies. The ideal candidate will possess extensive experience in building recommender systems at scale in production and have expertise in Merlin Models, GPU-based recommender systems, collaborative filtering, content-based filtering, matrix factorization, and the Azure Databricks ecosystem with ML Flow proficiency.

Responsibilities: 

Design, develop, and deploy scalable machine learning models for recommendation systems.

Collaborate with cross-functional teams to gather requirements and define project objectives.

Leverage Merlin Models for effective recommendation engine development.

Implement GPU-based recommender systems for efficient and high-performance recommendations in production.

Apply collaborative filtering, content-based filtering, and matrix factorization techniques to enhance the recommendation engine's performance.

Utilize the Azure Databricks ecosystem and ML Flow for seamless integration, model deployment, and monitoring.

Continuously improve the recommendation engine's performance through experimentation, optimization, and regular updates.

Develop and maintain documentation, including project plans, system architecture, and user guides.

Stay up-to-date with the latest advancements in machine learning, recommendation systems, and industry trends to ensure the company remains at the forefront of innovation. 

Requirements:

Bachelor's degree in Computer Science, Engineering, or a related field (Master's degree preferred).

5+ years of experience in machine learning engineering, with a focus on recommendation systems.

Proven experience building and deploying recommender systems at scale in production.

Deep understanding of Merlin Models, GPU-based recommender systems, collaborative filtering, content-based filtering, and matrix factorization.

Proficiency in the Azure Databricks ecosystem and ML Flow.

Strong programming skills in Python or similar languages.

Familiarity with machine learning frameworks, such as PyTorch.

Excellent problem-solving, analytical, and communication skills.

Ability to work effectively in a fast-paced, dynamic environment, both independently and as part of a team.

Thanks, and Regards

Amiksha Sharma

[email protected]

Call to: (609) 360-2660

https://www.linkedin.com/in/amikshasharma/

Ampstek Global IT Partner

www.ampstek.com

See what's happening on our social sites      

Organization Name
|
103 Carnegie Center Drive,
,
Suite 300,
,

Princeton, NJ 08540

Update Profile |
Constant Contact Data Notice

Sent by
[email protected]

powered by

Try email marketing for free today!

Keywords: machine learning information technology New Jersey
http://bit.ly/4ey8w48
https://jobs.nvoids.com/job_details.jsp?id=710776&uid=
[email protected]
View All
12:37 AM 04-Oct-23


To remove this job post send "job_kill 710776" as subject from [email protected] to [email protected]. Do not write anything extra in the subject line as this is a automatic system which will not work otherwise.


Your reply to [email protected] -
To       

Subject   
Message -

Your email id:

Captcha Image:
Captcha Code:


Pages not loading, taking too much time to load, server timeout or unavailable, or any other issues please contact admin at [email protected]


Time Taken: 8

Location: Dallas, Texas