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Machine Learning Research Engineer Job Opening In – Now Hiring Numerator


Job description

Numerator is looking for a passionate Engineer to join our growing Research and Development team.

This is a unique opportunity where you will get a chance to work with an established and rapidly evolving platform that handles millions of requests and massive amounts of events, and other data.

In this position, you will be responsible for taking on new initiatives to design, build, deploy, and support high performance deep learning systems in a rapidly-scaling environment.



As a member of our team, you will make an immediate impact as you help build out and expand our technology platforms across several software products.

This is a high growth and impact role that will give you tons of opportunity to drive decisions for projects from inception through production.

What You'll Do:
+ Help to create and build out our API framework that enables our machine learning team to expose their models to engineering teams across the organization.
+ Orchestrate systems using Kubernetes.
+ Set up CI/CD pipelines of multiple applications.
+ Scale multiple APIs to handle millions of requests per day using both synchronous and asynchronous webhook callback approaches.
+ Work with deep learning engineers and DevOps teams to troubleshoot server/infrastructure/systems-level issues.
+ Assist in data gathering and enhancing and building out visualizations to help QC model output.
+ Maintaining the system in general, on-call bug-fixing for mission critical issues.
+ Work on and build out tools that simplify package upgrades across many microserves
+ 3+ years experience deploying robust APIs in production environments (ideally cloud-based environments such as AWS or GCP).
+ Knowledge of deploying and troubleshooting containers (Docker) and container orchestration systems (Kubernetes).
+ 2+ years Experience with python and web frameworks like django, flask or FastAPI.
+ An understanding of the importance of CI/CD pipelines.
+ You look ahead to identify opportunities and foster a culture of innovation.
+ BS in Computer Science or a related field, or equivalent work experience.





Nice to Haves:
+ Knowledge of Terraform or other infrastructure as code solutions.
+ Experience working with Amazon web services or another cloud provider.
+ Experience deploying and working on Kubernetes clusters on EKS.
+ Knowledge of monitoring, tracing, and metrics visualization (e.g. Prometheus, Sentry, Fluentd, Grafana, OpenTracing,/Jaeger, etc)
+ Production experience with deep learning systems (e.g. inference optimization, GPUs)




What We Offer:
+ An inclusive and collaborative company culture
+ An opportunity to have an impact on our growing teams and organization
+ Ownership of platforms and environments with industry leading products
+ Market competitive total compensation package
+ Volunteer time off and charitable donation matching
+ Strong support for career growth, including mentorship programs, leadership training, and access to employee resource groups
+ Regular hackathons to build your own projects and work with people across the entire company
+ Excellent benefits package including medical/vision/dental insurance, unlimited PTO, and 401k plus matching.





Required Skill Profession

Other General


  • Job Details

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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning Jobs Trends (Graphical Representation)

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Are You Looking for Machine Learning Research Engineer Job?

Great news! is currently hiring and seeking a Machine Learning Research Engineer to join their team. Feel free to download the job details.

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Numerator adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

What Is the Average Salary Range for Machine Learning Research Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in . Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Machine Learning Research Engineer?

Key qualifications for Machine Learning Research Engineer typically include Other General and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Machine Learning Research Engineer Job Success

Numerator interview tips for Machine Learning Research Engineer

Here are some tips to help you prepare for and ace your Machine Learning Research Engineer job interview:

Before the Interview:

Research: Learn about the Numerator's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Machine Learning Research Engineer interview at Numerator, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Numerator's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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