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Dynamic Technical Formulations Jobs in California

MeriCal, LLC

Process Engineer, Tech Ops

Orange, CA · On-site

$135K - $140K/yr

Join us and be part of a dynamic, forward-thinking team shaping the future of nutrition! The ... This role owns the technical performance of dry-fill, compression, encapsulation, blending ...

Merical, Llc

Process Engineer, Tech Ops

Orange, CA · On-site

$125 - $150/hr

Join us and be part of a dynamic, forward-thinking team shaping the future of nutrition ... The Opportunity: The Process Engineer, Technical Ops is responsible for optimizing and ...

Socket.dev

Process Engineer, Tech Ops

Orange, CA · On-site

$125 - $150/hr

Join us and be part of a dynamic, forward-thinking team shaping the future of nutrition ... The Opportunity: The Process Engineer, Technical Ops is responsible for optimizing and ...

Pharmavite

Formulator

Valencia, CA · On-site

$74K - $124K/yr

Providing technical and scientific input, support , and assistance to other technical disciplines ... Partnering cross-functionally to improve formulations, evaluate alternate raw materials, and ...

Nautilus Bio

NPI Scientist San Carlos

San Carlos, CA · On-site

$125 - $150/hr

... dynamic and valuable sources of biological insight. To accomplish this, we are pursuing hard ... formulations and processes. * Author documents including SOPs, batch records, and technical reports ...

Pharmavite

Formulator

Valencia, CA · On-site

$74K - $124K/yr

Providing * technical and scientific input, support,and assistance to other technical disciplines ... Partneringcross-functionally to improve formulations, evaluate alternate raw materials, and support ...

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Showing results 41-60

All JobsDynamic Technical Formulations JobsDynamic Technical Formulations Jobs in California

Dynamic Technical Formulations information

See California salary details

$26.6K

$42.9K

$65.1K

How much do dynamic technical formulations jobs pay per year?

As of Sep 7, 2026, the average yearly pay for dynamic technical formulations in California is $42,911.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,000.00 and $46,400.00 per year, depending on experience, location, and employer.

What is a dynamic technical formulation?

Dynamic Technical Formulations refer to the specialized process of creating and optimizing technical mixtures, compounds, or recipes—often in industries like pharmaceuticals, chemicals, or materials science. Professionals in this field design, test, and refine formulas to achieve desired properties and performance based on evolving needs or technological advances. This work often involves interdisciplinary knowledge of chemistry, engineering, and data analysis to ensure formulations are safe, effective, and scalable for manufacturing. Dynamic Technical Formulations are crucial for developing new products or improving existing ones to meet regulatory standards and market demands.

What skills and qualifications are needed to thrive as a dynamic technical formulation specialist?

To thrive as a Technical Formulation Specialist, you need a strong background in chemistry or chemical engineering, with experience in product development and formulation techniques, often supported by a relevant degree. Familiarity with laboratory equipment, formulation software, and regulatory compliance systems is typically expected. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for collaborating with cross-functional teams and ensuring product quality. These skills and qualifications are crucial for developing safe, effective, and innovative products that meet industry standards and client needs.

How does a dynamic technical formulation specialist typically collaborate with R&D and production teams during product development?

A Dynamic Technical Formulations specialist works closely with both research and development (R&D) and production teams to ensure that new formulations are not only innovative but also manufacturable at scale. This collaboration often involves translating lab-scale recipes into robust, cost-effective manufacturing processes, troubleshooting technical challenges, and ensuring compliance with industry standards. Regular meetings, joint problem-solving sessions, and cross-functional projects are common, allowing specialists to provide technical guidance and incorporate feedback from multiple departments. Effective communication and adaptability are key to successfully aligning formulation goals with production capabilities.

What is the difference between Dynamic Technical Formulations vs Chemical Laboratory Technician?

AspectDynamic Technical FormulationsChemical Laboratory Technician
Required CredentialsBachelor's degree in Chemistry or Chemical EngineeringAssociate's degree or diploma in Chemistry or related field
Work EnvironmentResearch and development labs, manufacturing settingsLaboratories, quality control labs
Industry UsagePharmaceutical, cosmetics, specialty chemicalsManufacturing, quality assurance, testing
Job FocusFormulating and developing new products or processesTesting, analyzing, and ensuring product quality

Dynamic Technical Formulations professionals focus on creating and optimizing formulations for various products, often in R&D settings. Chemical Laboratory Technicians primarily perform testing and analysis to ensure product quality. While both roles require chemistry knowledge, their responsibilities and work environments differ significantly.

What are popular job titles related to Dynamic Technical Formulations jobs in California?

For Dynamic Technical Formulations jobs in California, the most frequently searched job titles are:

What job categories do people searching Dynamic Technical Formulations jobs in California look for?

The top searched job categories for Dynamic Technical Formulations jobs in California are:

What cities in California are hiring for Dynamic Technical Formulations jobs?

Cities in California with the most Dynamic Technical Formulations job openings:

Dynamic Technical Formulations jobs near you
Infographic showing various Dynamic Technical Formulations job openings in California as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, 2% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $42,911 per year, or $20.6 per hour.

Senior Computer Vision Algorithm/Software Engineer

SAAZ Micro Inc

Camarillo, CA • On-site

$125K - $164K/yr

Full-time

Posted 24 days ago

Job description

SAAZ is seeking an exceptional Senior Computer Vision Algorithm & Software Engineer to architect and implement advanced processing pipelines for next-generation electro-optical and infrared (EO/IR) imaging systems.
This multidisciplinary role bridges theoretical research and high-performance software engineering, requiring hands-on expertise in image processing, computer vision, convolutional neural networks (CNNs), or spiking neural networks (SNNs) rather than traditional application software development alone. Operating with a high degree of autonomy, the successful candidate will hold a graduate degree-preferably a PhD-and possess the independent drive to conceptualize, design, and deploy sophisticated algorithms from scratch without direct supervision.
Working closely with Firmware, FPGA, Systems, and Product Engineering teams, you will drive algorithmic innovation for advanced camera products deployed in aerospace, defense, and commercial imaging, guiding developments from concept through hardware-software integration and production.
Key Responsibilities:
  • Algorithm Architecture & Conceptualization: Design, prototype, and refine advanced image processing and computer vision algorithms-including traditional image enhancement, noise reduction, and modern deep learning models (CNNs/SNNs)-tailored for EO/IR sensor architectures.

  • Autonomous End-to-End Implementation: Independently translate mathematical models and theoretical concepts into high-performance, maintainable software implementations without needing direct step-by-step supervision.

  • Cross-Functional System Integration: Collaborate closely with Firmware, FPGA, and Systems Engineering teams to optimize, port, and validatealgorithms on real-time target hardware and embedded camera processing platforms.

  • EO/IR Pipeline Optimization: Develop and tune edge-detection, feature extraction, non-uniformity correction (NUC), dynamic range expansion, object detection
    and tracking algorithms specialized for complex electro-optical and infrared environments.

  • Research & Feasibility Trade Studies: Conduct independent trade studies, literature reviews, and rapid prototyping to evaluate novel machine learning and spiking neural network (SNN) approaches for low-power or bandwidth-constrained imaging systems.

  • Verification & Testing Pipelines: Build robust simulation environments, ground-truth dataset collection methodologies, and automated testing frameworks to evaluate algorithm accuracy, latency, and performance edge cases.

  • Technical Documentation & Mentorship: Document mathematical formulations, algorithmic trade-offs, and software architectures to support production handover, system qualification, and intellectual property development.

Minimum / Required Qualifications:
  • Education & Experience: Master's degree in Electrical Engineering, Computer Science, Applied Mathematics, Optical Engineering, or a closely related field with 5+ years of hands-on algorithmic experience, or a Ph.D. with 2+ years of relevant research/industry experience.
  • Domain Expertise: Proven hands-on track record developing and deploying core image processing, computer vision, or neural network models (CNNs or SNNs). Pure application software development without signal processing or computer vision experience will not be considered.
  • EO/IR Pipeline Knowledge: Direct familiarity with physical imaging concepts and sensor data pipelines, such as non-uniformity correction (NUC), bad pixel replacement, dynamic range compression, or thermal/optical noise reduction.
  • Core Technical Stack: Proficiency in C/C++ and Python for rapid prototyping, algorithm implementation, and performance benchmarking.
  • Mathematical Foundations: Strong foundation in linear algebra, multi-variable calculus, spatial/frequency-domain filtering, and statistical signal processing.
  • Autonomous Execution: Demonstrated ability to drive projects independently from literature review and mathematical formulation through to functional code without daily supervision.

Preferred Qualifications:
  • Advanced Degree: Ph.D. focusing on Computer Vision, Spiking Neural Networks (SNNs), Neuromorphic Computing, or Infrared Image Processing.
  • Hardware-Aware Software Optimization: Experience adapting heavy algorithmic models or neural networks for resource-constrained platforms, such as embedded GPUs (NVIDIA Jetson), FPGAs, or specialized DSP architectures.
  • Advanced Neural Architectures: Hands-on research or deployment experience with Spiking Neural Networks (SNNs), event-based neuromorphic sensors, or ultra-low-latency event processing for edge execution.
  • Specialized EO/IR Algorithms: Background in real-time object detection/tracking, multi-sensor data fusion (EO/IR registration), or high dynamic range (HDR) image reconstruction.
  • Simulation & Frameworks: Expertise with deep learning and vision frameworks (e.g., PyTorch, OpenCV, TensorRT, LibTorch) alongside customized C++ execution pipelines.

Success Metrics:
  • Algorithms execute within defined latency, framerate, and real-time processing constraints.
  • CPU, GPU, and embedded memory utilization remain within target resource budgets.
  • Algorithms achieve specified precision, recall, and detection/tracking accuracy metrics across target EO/IR datasets.
  • Code passes performance, memory leak, and static analysis checks without critical warnings or errors.
  • Compliance with project coding, testing, and documentation standards.
  • Unit, integration, and ground-truth simulation tests successfully completed.
  • Seamless pipeline integration and data throughput achieved across cross-functional interfaces (Firmware, FPGA, host APIs).
  • Algorithmic robustness validated under adverse real-world conditions (e.g., thermal drift, low contrast, high dynamic range, atmospheric noise).

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