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Machine Learning Engineer Job Opening In Richardson – Now Hiring Tiger Analytics


Job description

Tiger Analytics is a global AI and analytics consulting firm.

With data and technology at the core of our solutions, we are solving problems that eventually impact the lives of millions globally.

Our culture is modeled around expertise and respect with a team-first mindset.

Headquartered in Silicon Valley, you’ll find our delivery centers across the globe and offices in multiple cities across India, the US, UK, Canada, and Singapore, including a
substantial remote global workforce.

We’re Great Place to Work-Certified™.

Working at Tiger Analytics, you’ll be at the heart of an AI revolution.

You’ll work with teams that push the boundaries of what is possible and build solutions that energize and inspire.

We are seeking a highly skilled MLE/MLOps Engineer with a strong programming background and solid experience in software engineering practices.

The ideal candidate will play a critical role in building and maintaining robust machine learning infrastructure, ensuring seamless integration between ML models and production systems.

Requirements

  • Design, implement, and maintain scalable and reliable MLOps pipelines for model training, deployment, and monitoring.

  • Collaborate with data scientists and software engineers to productionize ML models.

  • Develop and maintain CI/CD workflows for ML systems and model lifecycle management.

  • Work with real-time data using Apache Spark Streaming to support high-throughput data processing pipelines.

  • Ensure high availability and performance of ML services in production.

  • Manage and automate infrastructure using tools such as Docker, Kubernetes, and Terraform.

  • Monitor and improve system performance, model drift, and data quality issues.

  • Implement best practices in software engineering including code reviews, testing, and documentation.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.

  • 7+ years of experience in software engineering / ML engineering with a strong programming foundation (Python, Java, or Scala).

  • Proven experience with MLOps tools and frameworks for model deployment and lifecycle management.

  • Hands-on experience with Apache Spark Streaming and real-time data processing.

  • Solid understanding of cloud platforms (preferably Azure).

  • Experience with version control (Git), containerization (Docker), and orchestration (Kubernetes).

  • Familiarity with CI/CD tools like Jenkins, GitHub Actions, or Azure DevOps.

Preferred Qualifications

  • Experience with Azure ML or other managed ML platforms (e.g., SageMaker, Vertex AI).

  • Exposure to ML model performance monitoring and alerting tools.

  • Knowledge of ML model testing, data validation, and reproducibility.

  • Experience working in an Agile development environment.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.


#LI-remote

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning 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 Machine Learning in Richardson, United States, highlighting market share and opportunities for professionals in Machine Learning roles.

11113 Jobs in United States
11113
6 Jobs in Richardson
6
Download Machine Learning Jobs Trends in Richardson and United States

Are You Looking for Machine Learning Engineer Job?

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

Wait no longer! Are you also interested in exploring similar jobs? Search now: .

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 Tiger Analytics 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 Engineer Positions?

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

Key qualifications for Machine Learning Engineer typically include Computer Occupations 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.

How Can I Improve My Chances of Getting Hired for Machine Learning Engineer?

To improve your chances of getting hired for Machine Learning Engineer, consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

Interview Tips for Machine Learning Engineer Job Success

Tiger Analytics interview tips for Machine Learning Engineer

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

Before the Interview:

Research: Learn about the Tiger Analytics'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 Engineer interview at Tiger Analytics, 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 Tiger Analytics'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!

How to Set Up Job Alerts for Machine Learning Engineer Positions

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