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ML Ops Engineer ID38029 – $3,000 Sign-On Bonus Job Opening In WorkFromHome – Now Hiring AgileEngine


Job description

Join to apply for the ML Ops Engineer ID38029 – $3,000 Sign-On Bonus role at AgileEngine

2 weeks ago Be among the first 25 applicants

Join to apply for the ML Ops Engineer ID38029 – $3,000 Sign-On Bonus role at AgileEngine

Join us and receive a $2,500 sign-on bonus!
AgileEngine is an Inc.

5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries.

We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

WHAT YOU WILL DO
- ML Infrastructure Support and Development: Build and maintain scalable ML infrastructure on Databricks, leveraging Unity Catalog and feature stores to support model development and deployment;
- Drift Detection Frameworks: Design and implement frameworks for detecting data and model drift, ensuring continuous monitoring and high reliability of ML models in production;
- Model Calibration & Versioning: Develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle;
- Low-Latency Orchestration: Design and optimize reinforcement learning (RL) orchestration pipelines, including Contextual Bandits, for real-time execution in low-latency environments;
- Automated Training Pipelines: Create automated frameworks for training, retraining, and validating ML models, enabling efficient experimentation and deployment;
- CI/CD for ML: Implement CI/CD best practices to streamline the deployment and monitoring of ML models, integrating with Databricks workflows and Git-based version control systems;
- Collaboration: Work closely with ML Scientists to ship, deploy, and maintain models;
- Monitoring & Optimization: Build tools for model performance monitoring, operational analytics, and drift mitigation, ensuring reliable operation in production environments.
MUST HAVES
- 3+ years in MLOps, ML Engineering, Data Engineering or related roles, focusing on deploying and managing ML workflows in production environments;
- 5+ years of experience using Python ;
- Proficient in using Databricks (2-3 years), Apache Spark, ML Flow, Unity Catalog, and feature stores;
- Familiarity with ML lifecycle tools such as MLflow , Kubeflow , and Airflow ;
- Strong knowledge of Git workflows, CI/CD practices, and tools like GitLab or similar;
- Strong understanding of model performance monitoring, drift detection, and retraining workflows;
- Upper-Intermediate English level.

THE BENEFITS OF JOINING US
- Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Your application doesn't end here! To unlock the next steps, check your email and complete your registration on our Applicant Site .

The incomplete registration results in the termination of your process.

Seniority level

  • Seniority level

    Mid-Senior level

Employment type

  • Employment type

    Full-time

Job function

  • Industries

    IT Services and IT Consulting

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Required Skill Profession

Tecnología De Medición, Control Y Regulación


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Unlock Your ML Ops Potential: Insight & Career Growth Guide


Real-time ML Ops Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for ML Ops in WorkFromHome, Colombia, highlighting market share and opportunities for professionals in ML Ops roles.

1895 Jobs in Colombia
1895
1669 Jobs in Workfromhome
1669
Download Ml Ops Jobs Trends in Workfromhome and Colombia

Are You Looking for ML Ops Engineer ID38029 – $3,000 Sign On Bonus Job?

Great news! is currently hiring and seeking a ML Ops Engineer ID38029 – $3,000 Sign On Bonus 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 AgileEngine 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 Colombia laws and regulations

What Is the Average Salary Range for ML Ops Engineer ID38029 – $3,000 Sign On Bonus Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in WorkFromHome. 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.

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Key qualifications for ML Ops Engineer ID38029 – $3,000 Sign On Bonus typically include Tecnología De Medición, Control Y Regulación 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 ML Ops Engineer ID38029 – $3,000 Sign On Bonus Job Success

AgileEngine interview tips for ML Ops Engineer ID38029 – $3,000 Sign On Bonus

Here are some tips to help you prepare for and ace your ML Ops Engineer ID38029 – $3,000 Sign On Bonus job interview:

Before the Interview:

Research: Learn about the AgileEngine'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.

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

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

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Final Thought:

To prepare for your ML Ops Engineer ID38029 – $3,000 Sign On Bonus interview at AgileEngine, 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 AgileEngine'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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