Hybrid 3 days / week onsite at Jersey City, NJ, 07310 - 1st preference Boston, MA, 02210 / Dallas, TX, 75019 - 2nd preference

Rate as per location: Jersey City, NJ / Boston, MA - MAX PR: $78 Dallas, TX - MAX Rate: $68

CTH- must be eligible for conversion 2 rounds of interviews

Important Notes from Hiring Manager: Will be converting at a senior associate level Feedback - MUST have hands on experience with writing code, machine learning technologies, API development/python, pandas, numpy

Supplier Call Notes: Team - Tech Research and innovations team - they evaluate multiple usecases thrughout DTCC. Push the prototypes to Production.

1. Backfill Role - Needs candidates ASAP. 2. Building Gen AI Apps - RAG / Agentic Wokflows 3. Langchain / Langgraph - MUST have 4. Snowflake Cortex - nice to have 5. Interview - Candidate must be able to share screen and code sample Snippet. 6. Locations - Jersey City, NJ / Boston, MA / Dallas, TX

Bachelor's or Master's degree in computer science, Statistics, Data Science, or a related field. • 6+ years of experience in Machine Learning and Data Science. • Need stong background in Genertive AI (RAG/ Agentic AI apps) • Strong understanding of statistical methods, data structures, and algorithms. • Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs. • Experience developing and deploying AI solutions on cloud platforms (e.g., AWS, Azure, or GCP).

Responsibilities: Generative AI Application Development • Develop and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs). • Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals. • Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities.

Model Development and Deployment • Design and develop machine learning models and algorithms to address business challenges and improve product features. • Deploy machine learning models in production environments to ensure scalability and efficiency. • Optimize and refine models based on performance metrics and feedback. Data Management • Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation. • Implement data augmentation and feature engineering techniques to enhance model performance. • Maintain and manage data pipelines to ensure seamless data flow and integration. Research and Innovation • Stay updated with the latest trends and advancements in AI and machine learning technologies. • Conduct research to explore new methodologies and techniques that can be applied to current and future projects. • Collaborate with cross-functional teams to drive innovation and implement cutting-edge solutions. Collaboration and Communication • Work closely with software engineers, data scientists, and product managers to align AI/ML initiatives with business goals. • Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner. • Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.

Qualifications • Bachelor's or Master's degree in computer science, Statistics, Data Science, or a related field. • 6+ years of experience in Machine Learning and Data Science. • Strong understanding of statistical methods, data structures, and algorithms. • Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs. • Experience developing and deploying AI solutions on cloud platforms (e.g., AWS, Azure, or GCP). • Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions. • Proven experience in developing and deploying machine learning models in a production environment. • Experience working with large datasets and performing data analysis. • Previous experience in a similar role or industry is preferred. • Excellent communication and collaboration skills. • Strong problem-solving skills and analytical thinking Passion for learning and staying up-to-date with the latest advance

EEO: "Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."