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SeniorFull-timePythonAzureKubernetesMachine LearningData ScienceTensorFlowPyTorchCI/CDGitAI
Salary Range
$26,520 - $35,880 /year
This salary is estimated based on similar roles. The actual salary may vary.
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
Specialization
• Data Science Advanced: Data Specialist
Job requirements
• Key Responsibilities • Design, implement, and manage scalable machine learning (ML) pipelines using Azure ML, Databricks, and PySpark. • Build and maintain automated CI/CD pipelines with Github and Github Action, incorporating SonarQube to ensure code quality and security standards. • Utilize Azure Kubernetes Service (AKS) to containerize and deploy machine learning models, ensuring high availability and scalability. • Have understanding of over all architecture and can work on scalable solutions • Develop reusable templates for various ML use cases to streamline the model deployment process and enhance operational efficiency. • Design and manage APIs to facilitate seamless interaction between ML models and other applications, ensuring robust, secure, and scalable API interfaces. • Perform model optimization, monitor data drift, data refresh checks, and ensure the ML pipelines are cost-efficient. • Implement cost monitoring and management strategies to ensure efficient use of resources, particularly for model training and deployment phases. • Work closely with data scientists, DevOps, and IT teams to deploy and manage machine learning models across environments. • Provide thorough documentation for ML workflows, pipeline templates, and optimization strategies to support cross-team collaboration.
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About Brillio 2
Brillio 2 is a forward-thinking technology and consulting firm specializing in digital transformation, software development, and IT services. Operating at the intersection of innovation and practicality, the company leverages cutting-edge technologies to help organizations navigate the complexities of the modern digital landscape. While the "2" in its name may suggest a focus on second-generation solutions or a renewed approach to technology, Brillio is rooted in a commitment to delivering scalable, efficient, and future-ready solutions to its clients. Headquartered in the United States, Brillio has established a global presence, serving clients across various industries with a mission to drive meaningful change through technology. Brillio 2 offers a comprehensive suite of services, including custom software development, cloud computing, AI and machine learning integration, and process automation. Key features of their offerings include agile methodologies, end-to-end project management, and a strong emphasis on cybersecurity and data privacy. Their target audience primarily consists of mid-sized to large enterprises seeking to optimize operations, enhance customer experiences, and stay competitive in rapidly evolving markets. By combining technical expertise with industry-specific insights, Brillio tailors its solutions to address unique business challenges, ensuring measurable outcomes for its clients. Notable for its client-centric approach and technical excellence, Brillio has built a reputation as a trusted partner in the digital transformation space. The company differentiates itself through a culture of innovation, a highly skilled workforce, and a track record of successful implementations across sectors such as finance, healthcare, and retail. Brillio’s unique value proposition lies in its ability to bridge the gap between emerging technologies and practical business applications, enabling organizations to achieve sustainable growth and operational efficiency.
