Job Description
Job description: - Position : Data Scientists - 1 Tech Lead a Headcount: 1 Salary range: 130-140 K ? AI/ML Lead Engineer (8+ yrs Years Experience) ? Key Responsibilities Full ML Lifecycle Management: Drive projects from initial ideation to production deployment, including data pipeline development, model training, validation, and serving. LLM & Agentic Development: Design, implement, and optimize solutions utilizing Large Language Models (LLMs) and developing sophisticated Agentic AI systems to solve complex business problems. Platform Expertise: Leverage and integrate core generative AI platforms, including Gemini and Amazon Bedrock , to build scalable and efficient solutions. MLOps & Tools: Implement MLOps best practices, utilizing tools like MLFlow for experiment tracking, model versioning, and pipeline orchestration. Quality Assurance: Develop and execute comprehensive testing strategies for LLM applications, including utilizing frameworks like DeepEval for prompt engineering and model output quality. Analytical Skill: Apply strong analytical skills to evaluate model performance, diagnose issues, and iterate on solutions to achieve maximum business impact. Collaboration: Work closely with cross-functional teams (data scientists, product managers, and software engineers) to define requirements and deliver integrated AI features. ? Required Qualifications Experience: 8+ years of professional experience in Machine Learning Engineering, AI Development, or a closely related field. Education: Master's degree in Computer Science, Data Science, Engineering, or a quantitative field. Technical Proficiency: Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn). Proven experience in deploying models on major cloud platforms (GCP, AWS, or Azure). Deep understanding of the architecture and fine-tuning of Large Language Models. Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow ) and validation frameworks (e.g., DeepEval ). Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions. Preferred Qualifications Hands-on experience developing applications or services using Google's Gemini API or models. Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock . Experience in building and managing multi-step, reasoning-based Agentic AI systems. Prior experience in optimizing models for latency and cost efficiency in a production environment. Position : AI ML Engineer Headcount: 3 Salary range: 110-120 K ? AI/ML Engineer - Mid-Level (7+ Years Experience) Overview We are seeking an innovative and results-oriented Mid-Level AI/ML Engineer to join our dynamic team. This role is crucial for transforming Client concepts into robust, production-ready AI solutions. The ideal candidate possesses a strong background in Machine Learning engineering, extensive experience with cutting-edge LLMs and cloud-based AI services, and a commitment to maintaining high-quality, responsible AI systems. ? Key Responsibilities Full ML Lifecycle Management: Drive projects from initial ideation to production deployment, including data pipeline development, model training, validation, and serving. LLM & Agentic Development: Design, implement, and optimize solutions utilizing Large Language Models (LLMs) and developing sophisticated Agentic AI systems to solve complex business problems. Platform Expertise: Leverage and integrate core generative AI platforms, including Gemini and Amazon Bedrock , to build scalable and efficient solutions. MLOps & Tools: Implement MLOps best practices, utilizing tools like MLFlow for experiment tracking, model versioning, and pipeline orchestration. Quality Assurance: Develop and execute comprehensive testing strategies for LLM applications, including utilizing frameworks like DeepEval for prompt engineering and model output quality. Analytical Skill: Apply strong analytical skills to evaluate model performance, diagnose issues, and iterate on solutions to achieve maximum business impact. Collaboration: Work closely with cross-functional teams (data scientists, product managers, and software engineers) to define requirements and deliver integrated AI features. ? Required Qualifications Experience: 4-7 years of professional experience in Machine Learning Engineering, AI Development, or a closely related field. Education: Master's degree in Computer Science, Data Science, Engineering, or a quantitative field. Technical Proficiency: Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn). Proven experience in deploying models on major cloud platforms (GCP, AWS, or Azure). Deep understanding of the architecture and fine-tuning of Large Language Models. Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow ) and validation frameworks (e.g., DeepEval ). Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions. Preferred Qualifications Hands-on experience developing applications or services using Google's Gemini API or models. Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock . Experience in building and managing multi-step, reasoning-based Agentic AI systems. Prior experience in optimizing models for latency and cost efficiency in a production environment. Additional Job Details: About Tanisha Systems, Inc. Tanisha Systems, founded in 2002 in Massachusetts- , is a leading provider of Custom Application Development and end-to-end IT Services to clients globally. We use a client-centric engagement model that combines local on-site and off-site resources with the cost, global expertise and quality advantages of off-shore operations. We deliver Custom Application Development, Application Modernization, Business Process Outsourcing and Professional IT Services from office locations in and . Tanisha Systems services clients in Government, Banking & Financial Markets, Insurance, Healthcare, Retail & Consumer Goods, Energy & Utilities, Life Sciences, Telecom, Manufacturing and Transportation Industries around the globe. Our engagement model provides a flexible operational environment that empowers our clients with the right levels of control. Want to read more about Tanisha Systems? Visit us at Website Open Jobs