Bayesian Optimization Jobs in Emerson, NJ (NOW HIRING)

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

You will move beyond simple predictive models to build transformative algorithmic solutions using Bayesian Black Box optimization, Contextual Bandits, and Deep Q-Networks (DQN/DDQN). The problem ...

... and Bayesian optimization. You will work on developing agents that can learn efficient policies in complex, partially observable environments by leveraging structured world models. The immediate ...

Bayesian optimization loops, experiment scheduling, long-running job execution, retries, idempotency * Data pipelines for ingesting, transforming, and serving data to models and LLMs What We're ...

Bayesian optimization loops, experiment scheduling, long-running job execution, retries, idempotency * Data pipelines for ingesting, transforming, and serving data to models and LLMs What We're ...

Bayesian optimization loops, experiment scheduling, long-running job execution, retries, idempotency * Data pipelines for ingesting, transforming, and serving data to models and LLMs What We're ...

Familiarity with Bayesian optimization, design of experiments (DoE), or active learning methods in applied settings Why This Role * Applied ML that reaches the real world: Your work accelerates R&D ...

Design and iterate models that estimate fair market value, recovery potential, and optimal ... Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling)

Python, Algorithms, Optimisation, NLP, Data Mining, Statistical Analysis, Neural Networks ... Bayesian inference) - ML & DS (e.g., dimensionality reduction, geometry of PCA / SVD and of L1 / L2 ...

Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods. * Develop portfolio construction and optimization techniques and analysis tools to be ...

Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods. * Develop portfolio construction and optimization techniques and analysis tools to be ...

Familiarity with Black-Litterman, shrinkage estimators, robust optimization, or Bayesian approaches to portfolio construction * Familiarity with hierarchical risk parity, equal risk contribution, or ...

... optimization problems, statistical modelling including Bayesian model fitting, DSP, control systems • Constraint modeling frameworks (Pyomo) and commercial/open-source solvers (HiGHS, Gurobi, GLPK ...

High-performance model implementation (vectorization, profiling/optimization); familiarity with PyTorch or JAX * Ecological modeling methods: agent-based, ODE/PDE, network, and Bayesian/statistical ...

Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting, DSP, control systems * Constraint modeling ...

Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting, DSP, control systems * Constraint modeling ...

Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting, DSP, control systems * Constraint modeling ...

Familiarity with Black-Litterman, shrinkage estimators, robust optimization, or Bayesian approaches to portfolio construction * Familiarity with hierarchical risk parity, equal risk contribution, or ...