Job Description
Day to day:
Partner with Digital Products & Analytics teams, business stakeholders, and SMEs to design, develop, and implement Machine Learning and Generative AI solutions. This person will build and deploy predictive models and GenAI applications, leverage structured and unstructured data to solve business problems, and drive measurable impact across operational and commercial use cases. They will also communicate findings to leadership, support productionized solutions, and help identify emerging AI technologies and best practices.
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Responsibilities:
• Develop Machine Learning and Generative AI solutions to solve complex business problems
• Build applications leveraging LLMs, vision models, embeddings, and traditional ML models
• Perform statistical analysis and advanced modeling using large structured and unstructured datasets
• Work with MLOps and platform teams to deploy, monitor, and optimize production models
• Partner closely with business stakeholders to understand needs and deliver impactful solutions
• Present insights, recommendations, and technical findings to both technical and non-technical audiences
• Research, evaluate, and promote emerging AI, GenAI, and Machine Learning tools and best practices across the organization
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
Must Haves:
• Bachelor's degree in Engineering or a quantitative field (Statistics, Mathematics, Economics, Physical Sciences, Engineering)
• 1-2+ years of experience developing Machine Learning and Generative AI solutions
• Experience implementing supervised machine learning models on real-world tabular datasets
• Strong Python programming skills
• Experience with TensorFlow and/or PyTorch
• Strong SQL skills (Hive/Pig experience is also applicable)
• Experience with application development tools such as Docker, Django, and Git
• Knowledge of Machine Learning algorithms including Classification, Regression, Clustering, Computer Vision, and NLP/NLU
• Experience with Deep Learning architectures and Large Language Models (LLMs)
• Hands-on experience with Azure OpenAI, AWS Bedrock, LangChain, LlamaIndex, Claude, Llama, or similar GenAI technologies
• Experience with prompt engineering, fine-tuning models, and building RAG (Retrieval-Augmented Generation) pipelines
• AWS experience including Bedrock, SageMaker, Redshift, Athena, S3, and Data Lakes
• Experience deploying and supporting models in production environments
• Strong verbal and written communication skills with the ability to explain technical concepts to business stakeholders
• Ability to work independently while collaborating effectively with SMEs, technical teams, and business partners
• Proven problem-solving skills and ability to identify opportunities that drive business impact
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.