AI Developer

Platinum Technologies

$145K — $165K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience).
  • 4+ years of experience developing AI/ML solutions, with experience in data science.
  • Hands-on experience across major cloud platforms (AWS, Azure, GCP).
  • Experience with multiple AI/ML model types not tied to a single vendor.
  • Strong programming skills in Python, with experience in ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience with data engineering fundamentals: SQL, data pipelines, data warehousing/lakes.
  • Must be eligible for a Public Trust clearance.

Responsibilities

  • Design and develop AI models and applications to solve business problems.
  • Collaborate to preprocess, clean, and analyze large datasets.
  • Implement machine learning and deep learning algorithms for production-ready solutions.
  • Fine-tune AI models for improved performance and efficiency.
  • Integrate AI models into production systems for reliability and scalability.
  • Document code and processes thoroughly for future maintenance.
  • Stay current with AI technologies and recommend beneficial adoptions.
  • Ensure solutions meet security and compliance requirements.

Benefits

  • Hybrid working model (2 days on-site, 3 days remote).
  • Eligibility for Public Trust clearance.
  • Professional development opportunities.
  • Access to the latest AI technologies and platforms.
Full Job Description
You

Platinum Technologies is seeking an experienced AI Developer with Data Science expertise to design, build, and deploy intelligent solutions across diverse technical environments. The ideal candidate is comfortable operating in multi-cloud, multi-platform, and model-agnostic settings - architecting AI/ML solutions that are portable, scalable, and not locked into a single vendor's ecosystem. This role blends hands-on AI/ML engineering with data science rigor, and requires the judgment to select the right cloud, platform, and model for the problem at hand rather than defaulting to a single toolchain.

Location: Washington, DC (Hybrid - 2 days on-site per week, 3 days remote)

Clearance Requirement: Must be eligible for Public Trust clearance (U.S. Citizenship or eligible status typically required)

Key Responsibilities

  • Design and develop AI models, algorithms, and applications to solve specific business or mission problems, across multi-cloud, multi-platform, and model-agnostic environments.


  • Collaborate with team members to preprocess, clean, and analyze large datasets in support of model development and evaluation.


  • Implement machine learning and deep learning algorithms and frameworks to build robust, production-ready AI solutions.


  • Fine-tune AI models to improve performance, accuracy, and efficiency for specific use cases.


  • Integrate AI models into production systems, ensuring reliability, scalability, and maintainability.


  • Document code, algorithms, and processes thoroughly for future reference - documentation must include all information necessary for another engineer to assume ongoing maintenance of the model or system (e.g., architecture decisions, data sources/lineage, dependencies, configuration, known issues, and retraining/monitoring procedures).


  • Stay current with the latest AI technologies, models, platforms, and frameworks, and recommend adoption where it benefits the organization.


  • Ensure solutions meet security, compliance, and data governance requirements appropriate to a Public Trust environment.


Required Qualifications

  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience).


  • 4+ years of experience developing AI/ML solutions, with demonstrated experience in data science (statistical modeling, predictive analytics, or similar).


  • Hands-on experience across at least two major cloud platforms (AWS, Azure, GCP).


  • Experience working with multiple AI/ML model types or providers in a way that is not tied to a single vendor (e.g., building abstraction layers, using orchestration frameworks like LangChain/LlamaIndex, or working across proprietary and open-source models).


  • Strong programming skills in Python (or similar), with experience in ML frameworks such as TensorFlow, PyTorch, or scikit-learn.


  • Experience with data engineering fundamentals: SQL, data pipelines, data warehousing/lakes.


  • Must be eligible for a Public Trust clearance (U.S. citizenship or otherwise eligible status generally required; ability to pass a background investigation).


  • Strong communication skills and ability to work effectively in a hybrid team environment.


Preferred Qualifications

  • Master's degree in a relevant technical field.


  • Experience with containerization and orchestration (Docker, Kubernetes) for portable AI deployments.


  • Familiarity with MLOps practices and tools (MLflow, Kubeflow, CI/CD for ML).


  • Prior experience supporting government, public sector, or regulated industry clients.


  • Relevant certifications (e.g., AWS/Azure/GCP AI or ML certifications, Certified Data Management Professional).


  • Experience with retrieval-augmented generation (RAG), agentic AI systems, or LLM fine-tuning/evaluation.


$145,000 - $165,000 a year

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