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Bayesian Optimization Jobs in Emerson, NJ (NOW HIRING)

Sr Software Engineer

New York, NY · On-site

$134K - $176K/yr

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

Sr Software Engineer

New York, NY · On-site

$134K - $176K/yr

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

Sr Software Engineer

New York, NY

$134K - $176K/yr

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

Improve existing strategies and portfolio optimization * Execution monitoring * Be a core ... Bayesian inference-as well as techniques for dealing with errors that can occur, such as auto ...

Improve existing strategies and portfolio optimization * Execution monitoring * Be a core ... Bayesian inference-as well as techniques for dealing with errors that can occur, such as auto ...

AI Researcher

New York, NY · On-site

$175K - $250K/yr

... optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian ...

... optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian ...

AI Researcher - Vatic Labs

Manhattan, NY · On-site

$175K - $250K/yr

... optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian ...

Senior AI/ML Engineer

New York, NY · On-site

$95K - $125K/yr

Use statistical inference (Bayesian and Markov Chain Monte Carlo methods) for probabilistic design ... Use constrained multi-objective optimization, and other computational methods for design space ...

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Showing results 21-40

Bayesian Optimization information

What is the difference between Bayesian Optimization vs Data Scientist?

AspectBayesian OptimizationData Scientist
Primary FocusOptimizing complex functions and hyperparametersAnalyzing data, building models, deriving insights
Required SkillsStatistics, probability, machine learning, programmingStatistics, programming, data analysis, visualization
Work EnvironmentResearch labs, AI/ML teams, R&D departmentsBusiness, tech companies, consulting firms
Common ToolsPython, R, Bayesian libraries (e.g., GPy, scikit-optimize)Python, R, SQL, visualization tools

Bayesian Optimization is a specialized technique used within machine learning and AI to efficiently tune hyperparameters or optimize functions. Data Scientists often utilize Bayesian Optimization as part of their toolkit but have broader responsibilities, including data analysis, modeling, and reporting. While Bayesian Optimization focuses on optimization tasks, Data Scientists work on understanding and interpreting data to inform business decisions.

What cities near Emerson, NJ are hiring for Bayesian Optimization jobs? Cities near Emerson, NJ with the most Bayesian Optimization job openings:
Infographic showing various Bayesian Optimization job openings in Emerson, NJ as of July 2026, with employment types broken down into 8% As Needed, 42% Full Time, 14% Part Time, 26% Temporary, 1% Contract, and 9% Nights. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution.

$134K - $176K/yr

Full-time

Re-posted 26 days ago


Job description

We are looking for a full-stack software engineer to build software to efficiently manage microgrids and other distributed energy resources. This is a great role for someone looking to build software that will change the future of the energy industry.
This role will report to our Director of Software Engineering and be based in our New York City office (Union Square area).
Key responsibilities will include:
  • Front-end development: build web applications with modern, interactive UIs for operators and customers
  • Architect and maintain high-performance backend services and APIs (FastAPI, PostgreSQL) to support real-time microgrid operations, telemetry data pipelines, and optimization workflows at scale
  • Develop and enhance financial modeling features, building reliable calculation engines and data integrations that support portfolio-level analysis and investment decision-making
  • Design and validate mathematical optimization models (MILP/LP) using Pyomo and commercial or open-source solvers (HiGHS, Gurobi) for generator dispatch and fleet-level maintenance scheduling, including heuristic approaches, OPH projection, and constraint-based planning
  • Build and extend simulation infrastructure (rolling dispatch, Monte Carlo scenario analysis) to validate optimization outputs, refine algorithmic approaches, and auto-tune model parameters against operational requirements
  • IoT and messaging pipelines: design and maintain scalable data ingestion, transformation, and event-driven pipelines (MQTT, AWS IoT, SQS, Sparkplug B)
  • System design: collaborate with product management and design to deliver robust software products that excite users and achieve business goals
  • Reliability & observability: implement logging, monitoring, and alerting for high availability microgrid software deployments
  • Collaboration: work with stakeholders across engineering, operations, and product to turn workflows into production-ready automation
  • Continuous improvement: assess and adopt new technologies to enhance performance, scalability, and maintainability

The Ideal Candidate
  • Bachelor's degree in Computer Science, Electrical Engineering, or related field preferred
  • 5+ years of experience with Python and JavaScript/TypeScript development
  • Energy experience and modeling, optimization
  • Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting, DSP, control systems
  • Constraint modeling frameworks (Pyomo) and commercial/open-source solvers (HiGHS, Gurobi, GLPK)
  • FastAPI and microservices experience
  • React for front-end development
  • PostgreSQL and relational database design
  • Experience with high-volume, time-series data processing
  • Experience with message brokers and IoT protocols (MQTT, Sparkplug B, AWS IoT Core)
  • Experience with SCADA platforms (e.g., Ignition or equivalent) and deployment and management of edge devices
  • Experience with SCADA/energy protocols such as Modbus, OpenADR, DNP3, or IEEE 61850
  • Excellent communication and collaboration skills to work across teams with evolving requirements

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.