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In this role, you will leverage your expertise to extract knowledge and insights from data, investigate complex business problems, design and implement solutions for ML models, optimize workflows, execute ML algorithms on larger-scale datasets, and collaborate with other stakeholders to deliver cutting-edge ML solutions.
Job Responsibility:
Design, develop, and maintain scalable software applications with complex Data/ ML solutions
monitor and evaluate the performance of ML models in production, making necessary adjustments
build and deploy RESTful APIs to serve ML models
partner with data scientists to translate model requirements into production-ready code
implement and optimize algorithms for data processing, feature extraction, and model training
conduct code reviews and provide feedback
participate in the full software development lifecycle
document processes, code, and model performance to ensure knowledge sharing
Requirements:
8+ years of experience as a Software Engineer, with a focus on Machine Learning
proven experience in building and scaling RAG applications using frameworks like Langchain, LLamaIndex in production
7+ years of Data & Analytics, specializing in the design and development of Data & ML pipelines and/or platforms
6+ years of hands-on experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn etc.) and ML algorithms (i.e., clustering, decision trees, boosting, etc.)
5+ years of experience with data preprocessing, feature engineering and model evaluation
5+ years of experience developing production-level software with one or more languages, such as Python, Java, or C++
5+ years of experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes)
proficiency in defining API routes using HTTP methods like GET, POST, PUT, DELETE, and adept at handling request parameters and body data
strong understanding of data structures, algorithms, and software design principles
Nice to have:
Exposure in implementing Gen AI and/or NLP-based solutions using LLMs
develop Agentic AI applications and automate the orchestration workflows using Vertex AI Agent Builder, Langgraph
familiarity with working in Dev/ML Ops model and CI/CD tools and infrastructure as a code (e.g., Jenkins, Docker, Kubernetes)
knowledge of implementing security mechanisms like OAuth2, JWT tokens, and basic authentication to safeguard API endpoints
advanced SQL skills for complex query writing, optimization, and database management
experience within an IT infrastructure domain and familiarity with telemetry/log data and concepts is highly desirable
experience implementing or maintaining Feature Stores
excellent problem-solving skills and a collaborative spirit that thrives in a team environment
strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders in an engaging manner
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