Direct client jobs
Location: Des Moines or Indianapolis- hybrid onsite either location
Duration : Through the end of the year- potential to extend or convert
About the job
The Systems Optimization and Decision Analytics (SODA) Team is seeking a curious, innovative, and results-driven Machine Learning Scientist to help advance our AI and predictive modeling capabilities. We focus on building scalable, intelligent systems that power optimization, planning, forecasting, and human-in-the-loop decision-making for global operations. This role will center around designing and deploying cutting-edge ML models—including probabilistic models, large language models (LLMs), and time-series or agent-
What You’ll Do
Research, prototype, and implement state-of-the-art ML models across a range of tasks: forecasting, optimization, planning, recommendation, and human-AI teaming.
Develop Models Using Advanced Methods Such As
Large Language Models (LLMs), foundation model fine-tuning, and prompt engineering.
Probabilistic modeling, Bayesian inference, and uncertainty-aware decision systems.
Reinforcement learning (RL), multi-agent systems, and decision intelligence architectures.
Generative modeling (e.g., diffusion models, VAEs, normalizing flows).
Time-series and forecasting models (e.g., Temporal Fusion Transformers, DeepAR, N-BEATS).
Graph neural networks (GNNs), especially for spatio-temporal and structured prediction tasks.
Causal inference, self-supervised learning, and contrastive representation learning.
Design and evaluate retrieval-augmented generation (RAG) and agentic workflows using LLMs.
Scale experimentation and model training pipelines using Databricks, MLflow, and Spark.
Partner with domain experts to frame complex, real-world challenges into solvable ML problems.
Produce clean, reproducible code with strong documentation and CI/CD integration.
What Skills You Need
MS or PhD in Computer Science, ML, Statistics, or a related field.
Experience developing and deploying modern ML systems in production settings.
Solid foundation in deep learning and probabilistic machine learning.
Hands-on experience with transformer-based architectures, LLMs, and adaptation methods (e.g., fine-tuning, LoRA, RAG).
Strong Python skills with experience in PyTorch, TensorFlow, scikit-learn, and Hugging Face.
Familiarity with Databricks, Spark, and distributed computing frameworks.
Understanding of model evaluation, uncertainty quantification, and scientific experiment design.
Nice To Have
Experience in applied reinforcement learning, causal inference, or simulation-to-real (sim2real) modeling.
Exposure to self-supervised and contrastive learning techniques.
Familiarity with federated learning or privacy-preserving ML approaches.
Ability to integrate ML systems into user-facing applications and decision platforms.
Background in supply chain, agriculture, or other complex operational domains.
About You
Passion for research and experimentation with a practical mindset for deployment.
Excellent written and verbal communication skills for diverse audiences.
Comfortable working independently and as part of a distributed, collaborative team.
Able to prioritize, manage ambiguity, and deliver impact in a fast-paced setting.
To apply for this job email your details to bala.s@saxonglobal.com