C

Software Developer

CYNET SYSTEMS

Full-timeOn-siteMid level$110k – $121kPasadenaPythonGoAWS

Freshness

Updated Today

Apply method

External listing page

Location

Woodland Hills, Los Angeles County

How this salary compares

This salary sits inside the current mid level market band and runs $17k below the median.

In range

Mid level salary band. Sample size: 86 live salary-bearing jobs. Range $70k – $310k. Middle 50% $115k – $173k. Median $133k. Current job $115k.

  • Range $70k – $310k
  • Middle 50% $115k – $173k
  • Median $133k
  • Current job $115k

$115k

$133k

86 jobs

Benchmarks use active DevJobBoard listings for the same experience level. Imported experience levels can be inferred, so treat the result as a market signal rather than authoritative compensation data.

Want the full picture? Explore the mid level salary guide.

Explore this Pasadena developer job at CYNET SYSTEMS. Review responsibilities, compensation, and application details before you apply.

Job Overview: Pay Range: $53/hr - $58/hr Requirement/Must Have: • Solid background in Data Science and Machine Learning (8+ years). • Hands-on experience with Generative AI / LLMs (6+ years). • Strong experience in Python programming (6+ years). • Latest advancements in GenAI, LLMs, and AI frameworks (6+ years). • Exposure to MLOps / deployment of AI models (Good to have). • Good to have healthcare experience. Responsibilities: • Design, develop, and deploy Generative AI solutions for client use cases. • Work on AI/ML model development, fine-tuning, and evaluation. • Build and maintain data pipelines and AI workflows using Python. • Apply Data Science techniques for data analysis, feature engineering, and model optimization. • Collaborate with cross-functional teams to integrate AI solutions into products/platforms. • Stay updated with the latest advancements in GenAI, LLMs, and AI frameworks. • Provide technical guidance and contribute to solution architecture discussions. Nice to Have: • Experience with cloud platforms (AWS/Azure/GCP) for AI workloads. • Exposure to MLOps / deployment of AI models. • Experience working in client-facing or product-based environments.

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