ML Engineer with LLM

Job ID: SRJ_7275Posted: Location: Sunnyvale, CAEmployment Type: 1099, C2C, W-2Industry: Computer SoftwareClient: WiproContact: Meghana GorusuCompany: SRI Tech SolutionsJob Title: ML Engineer with LLMLocation: Sunnyvale, CA(onsite)JobDescription:6-8 years of experience in machine learning and LLM, with a proven track record in image processing and analysis.Development and optimization of Computer Vision algorithms and ML models.Continuously refine ML models to improve accuracyCollaborate with cross-functional teams to integrateAI/MLfeatures into the application.Skill Requirements:Proven hands-on experience in Python programming.Proficient in programming languages relevant toAI/MLdevelopment ( TensorFlow, PyTorch).Strong proficiency in machine learning concepts and practical application.Familiarity with data analytics packages including pandas, NumPy, and scikit-learn.Intermediate knowledge in statistics for data analysis and interpretation.Ability to create insightful and visually appealing graphs using tools like Matplotlib or Seaborn.Collaborative mindset with excellent communication skills to work effectively in a team.Responsibilities:Develop and maintain Python-based applications, leveraging expertise in Python programming.Implement and optimize machine learning models for data analysis and insights generation.Utilize data analytics packages such as pandas, NumPy, and scikit-learn for efficient data manipulation and processing.Work collaboratively with cross-functional teams to understand business requirements and translate them into technical solutions.Apply intermediate knowledge in statistics to analyze and interpret complex datasets.Create visually appealing graphs and visualizations to communicate findings effectively.SRI Tech Solutions is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national origin or citizenship status or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria.