Data Science/Machine Learning Engineer (Remote, Continental United States)

About ICA, Inc. International Consulting Associates, Inc. is a rapidly growing company, located in the D.C./Metro area. We were founded in 2009 to assist government clients with evaluating and achieving their objectives. We have become a trusted advisor helping our clients by offering cutting-edge innovation and solutions to complex projects. Our small company has grown significantly, and we're overjoyed at the opportunity to expand yet again! We are results-focused and have a proven track record supporting federal agencies and large government services primes in three main areas: Research and Data Analysis, Advanced-Data Science, and Strategic Services. We currently support multiple analytics and research programs across HHS. At ICA, we believe our success starts with our people. We foster a collaborative "one team" environment where work-life balance isn't just talked about – it's prioritized. We're building dynamic, highly skilled teams in a welcoming and supportive atmosphere. If you're passionate about using your technical expertise to make a difference, we want to talk to you.

• We are looking for Data Science/ Machine Learning Engineers to join our growing team!
• About the Role
• As a Data Science/ Machine Learning Engineer at ICA, you will be at the forefront of applying machine learning techniques to solve complex problems and enhance our products and services. Your role will involve developing and implementing machine learning models, collaborating with cross-functional teams, and contributing to the advancement of our AI capabilities.
• About You
• You are a curious and driven Machine Learning Engineer with a strong foundation in Python and hands-on experience building and deploying ML models in cloud environments like AWS. You thrive on solving complex problems with multilayered data and enjoy optimizing algorithms for performance and scalability. Your collaborative mindset allows you to work seamlessly with data scientists, engineers, and product teams to bring intelligent solutions to life. You stay current with the latest ML techniques and tools, and you’re passionate about turning prototypes into production-ready systems that deliver real-world impact.
• Responsibilities Identify Opportunities: Collaborate with internal and external stakeholders to uncover and define data-driven opportunities that align with strategic business goals. Data Analysis & Modeling: Mine and analyze complex datasets from company and client databases to drive product and business optimization strategies, using both traditional statistical techniques and state-of-the-art machine learning approaches. Assess the effectiveness and accuracy of new data sources and data gathering techniques, including evaluating and implementing methods for acquiring and processing large volumes of text data. Perform data processing using State of the Art LLM Models and technologies Innovation & Strategy: Assess the effectiveness of new data sources and data gathering techniques, identifying ways to enhance the organization’s data strategy with novel ML and AI methods. Client-Facing Presentations: Develop compelling presentations and demos to showcase analytical solutions and insights to both technical and non-technical audiences, including clients and senior management. Predictive Modeling & Optimization: Use advanced statistical and machine learning approaches to drive improvements in customer engagement, product performance, and business processes. Model Monitoring: Establish processes and tools to track model performance, data accuracy, and reliability over time. Continuously iterate on models to meet evolving business needs and industry best practices. Required Qualifications 5+ years of overall professional experience in data science, analytics, or a related field. At least 2–3 years of hands-on experience specifically focused on Large Language Models (LLMs) and related techniques (e.g., fine-tuning, instruction tuning, prompt engineering). Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field. Technical Proficiency: Coding knowledge and experience with Python Proven ability to use statistical computer languages (Python, R, SQL, etc.) for data manipulation, analysis, and model development. Experience with Hugging Face Transformers, LangChain, Llama Index, and/or large-scale training frameworks Familiarity with LLM evaluation, interpretability, and best practices. Knowledge of ML and data mining techniques (Regression, Deep Learning, NLP, Time Series Analysis, , etc.). Familiarity with AWS services (Athena, S3, Glue, SageMaker, Bedrock) for scalable model development. NLP Techniques (NER, Information Extraction, Text Categorization, Document Parsing) Preferred: exposure to MLOps tools, big data technologies (Hadoop, Spark), or other cloud se

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