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Senior AI/ML Engineer - R01544842

About Brillio:


Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.

Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.


Senior AI/ML Engineer


Primary Skills
  • Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio


Job requirements
  • Role: Senior AI/ML Engineer
  • Years of Experience: 8+ years
  • Location: San Ramon, CA (Remote)

  • Drift Frame Work : Framework for detecting drift Automatically monitor track accuracy and trigger model retraining and notifications to restore previous accuracy levels.
  • ML Generalist: Data Scientist with MLOPS Development and maintenance of ML pipeline ML Engineer focusing on experimentation and tracking.

Responsibilities:
  • Model Development: Develop machine learning models and algorithms to solve business problems, leveraging techniques such as supervised learning, unsupervised learning, and deep learning.
  • Deployment and Integration: Deploy machine learning models into production environments and integrate them with existing systems and workflows.
  • Performance Optimization: Optimize machine learning models for scalability, efficiency, and performance, considering factors such as latency, throughput, and resource utilization.
  • Monitoring and Maintenance: Monitor model performance in production, identify and diagnose issues, and implement solutions to ensure continued reliability and effectiveness. Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to understand business requirements and deliver solutions that meet stakeholders' needs.
  • Research and Innovation: Stay up-to-date with the latest advancements in artificial intelligence and machine learning research, and explore new techniques and methodologies to improve model performance and capabilities.

  • Why should you apply for this role?
  • (Practice Pitch)
  • As Brillio continues to gain momentum as a trusted partner for our clients in their digital transformation journey, we strive to set new benchmarks for speed and value creation. The Advisory and Value Assurance (AVA) team at Brillio is at the forefront of leading this charge by reimagining and executing how we structure, sell and deliver our services to better serve our clients.
  •  
  • Know more about <add practice specific page link from Brillio website>
  • PPE: https://www.brillio.com/platform-and-product-engineering/
  • DAE: https://www.brillio.com/services-data-analytics/
  • CES: https://www.brillio.com/services-customer-experience-services/
  • DI: https://www.brillio.com/services-digital-infrastructure/
  •  
  • Know what it’s like to work and grow at Brillio:https://www.brillio.com/join-us/
  •  
  • Equal Employment Opportunity Declaration
  • Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation.


$60 - $67 an hour

 

Know what it’s like to work and grow at Brillio: Click here

Average salary estimate

$132120 / YEARLY (est.)
min
max
$124800K
$139440K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior AI/ML Engineer - R01544842, Brillio

Are you ready to take your career to the next level as a Senior AI/ML Engineer at Brillio in sunny San Ramon, California? Brillio is one of the fastest-growing digital technology service providers, proudly partnering with Fortune 1000 companies to help them leverage innovation and tackle the challenges of digital transformation. As a Senior AI/ML Engineer, you will dive into the fascinating world of machine learning, developing innovative models that address real business needs. This role requires a solid 8+ years of experience, a strong foundation in Python or PySpark, and familiarity with tools like TensorFlow and PyTorch. You will have the opportunity to leverage your skills in hypothesis testing, statistical analysis, and various ML frameworks to push the boundaries of what’s possible. In addition to model development, you'll be responsible for deployment, optimization, and maintaining the reliability of models in production. Collaboration is key, as you'll work closely with cross-functional teams to ensure the solutions we deliver meet our clients' expectations. At Brillio, we believe in nurturing our Brillians, so expect a work culture that fosters growth and innovation. If you’re passionate about making a difference in the AI/ML landscape and you thrive in a dynamic environment where your work will impact client success, we want you on our team!

Frequently Asked Questions (FAQs) for Senior AI/ML Engineer - R01544842 Role at Brillio
What responsibilities does a Senior AI/ML Engineer have at Brillio?

As a Senior AI/ML Engineer at Brillio, you will be responsible for developing machine learning models and algorithms to tackle various business challenges. You’ll engage in model deployment and integration into production environments while optimizing performance across scalability and efficiency. Additionally, monitoring and maintaining model performance, collaborating with cross-functional teams, and staying abreast of advancements in AI/ML are crucial aspects of your role.

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What qualifications are needed for the Senior AI/ML Engineer position at Brillio?

To qualify for the Senior AI/ML Engineer position at Brillio, candidates typically need 8+ years of experience in machine learning and data science. A deep understanding of techniques such as supervised and unsupervised learning, proficiency in programming languages like Python or PySpark, and familiarity with various ML frameworks like TensorFlow and PyTorch are essential.

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What kind of projects will I work on as a Senior AI/ML Engineer at Brillio?

In the Senior AI/ML Engineer role at Brillio, you will work on a variety of cutting-edge projects that apply machine learning techniques to solve pressing business problems. This includes developing models that enhance automated processes, improve customer experiences, and optimize operational efficiencies across diverse industries. Your contributions will directly impact Brillio's mission of driving digital transformation for our clients.

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Is the Senior AI/ML Engineer role at Brillio remote?

Yes, the Senior AI/ML Engineer position at Brillio offers remote work flexibility, allowing you to perform your duties from San Ramon, California. This arrangement is designed to adapt to the modern work environment and provide a balanced approach to productivity and personal life.

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What makes Brillio a great place to work for Senior AI/ML Engineers?

Brillio is recognized as a Great Place to Work® and attracts top talent due to its commitment to innovation and employee development. As a Senior AI/ML Engineer, you will have access to a collaborative culture, opportunities for professional growth, and the chance to work on meaningful projects. Brillio's emphasis on contemporary technologies ensures you will constantly be learning and adapting in this fast-paced field.

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Common Interview Questions for Senior AI/ML Engineer - R01544842
Can you explain your experience with machine learning frameworks like TensorFlow and PyTorch for the Senior AI/ML Engineer position?

In your answer, highlight specific projects where you utilized TensorFlow or PyTorch, detailing the challenges faced and how you solved them. Discuss your comfort level with building, training, and deploying models using these frameworks, emphasizing any performance optimizations you implemented.

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What methods do you use to monitor model performance in production?

Discuss your approach to model monitoring, including using metrics to evaluate accuracy and performance over time. Mention any tools or frameworks you have used to set up alerts for model drift or degradation and how you determine when retraining is necessary.

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How do you stay current with advancements in AI and machine learning?

Share how you engage with the AI/ML community. This could include attending conferences, participating in online forums, subscribing to relevant journals, and continuously learning through online courses. Mention how you apply this knowledge to enhance your work as an AI/ML Engineer.

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Can you describe a successful machine learning project you've worked on?

Provide a concise overview of a specific project, focusing on the problem it addressed, the solution you implemented, and the impact it had on the business. Highlight your role, the technologies used, and any quantitative metrics that demonstrate success.

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What is your approach to data preprocessing in machine learning?

Explain your process for data cleaning, transformation, and feature selection. Discuss the importance of these steps and how they impact model performance. You may also mention any tools or techniques you prefer for data preprocessing.

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How do you handle challenges when deploying machine learning models?

Discuss specific challenges you've encountered during deployment, such as integration with existing systems or scalability issues, and how you overcame them. Provide examples of how you collaborated with other teams to ensure successful deployment.

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What techniques do you use for model optimization?

Talk about common optimization techniques you employ, such as hyperparameter tuning, cross-validation, and feature engineering. Provide examples of when you've successfully optimized a model and the results that followed.

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How do you ensure your machine learning models are robust and reliable?

Discuss strategies that you use to validate and test models before deployment, including using holdout sets, K-fold cross-validation, and A/B testing to ensure robustness and reliability. Highlight the importance of continual monitoring post-deployment.

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Describe how you work within cross-functional teams to achieve project goals.

Provide examples of how you have collaborated effectively with data scientists, software engineers, and product managers. Discuss communication strategies and how you ensure that the team aligns with project objectives.

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What role does hypothesis testing play in your machine learning work?

Explain how you use hypothesis testing to evaluate model effectiveness or feature importance. Provide examples of statistical tests you've used and how their results influenced your decisions in model development.

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Full-time, remote
DATE POSTED
January 10, 2025

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