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Urgent! AI/ML Full Stack Engineer Job Opening In Washington Highlands District of Columbia – Now Hiring Mindlance



Job description

Title: AI/ML Full Stack Engineer

Duration: 9 Months - Long Term

Location: Washington, DC 20433

Hybrid Onsite: 4 Days per week onsite from Day1




Role and responsibilities:


  • Developing AI models: Building and fine-tuning machine learning models, including specialized ones like large language models (LLMs), to solve development challenges.


  • Engineering cloud applications: Designing and building cloud-native data and AI tools and ensuring they are scalable, secure, and performant.

    Client frequently uses cloud platforms like Azure, GCP, or AWS.


  • Building user interfaces: Developing the front-end user experience, including interactive data and knowledge dashboards.


  • Managing data infrastructure: Handling large, complex datasets, including data sourcing, cleaning, and preparation for model training.


  • Implementing best practices: Coordinating the technical work of data teams by conducting code reviews, implementing MLOps strategies, and ensuring ethical AI use .

  • Working with stakeholders: Collaborating with internal teams and external partners to gather requirements and present AI-driven solutions.





Required skills and qualifications:

To succeed in this position, you need a strong technical foundation and experience with both the AI and software development lifecycles.




  • Education: A master's degree or higher in a relevant field, such as Computer Science, Data Science, or Artificial Intelligence, is typically required.


  • Experience: A minimum of 7-10 years of professional experience in a related role is often requested.

    This should include hands-on experience in AI engineering and cloud-native application development.


  • Programming languages: Proficiency in Python is essential, along with experience using AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn.

    Strong skills in JavaScript/TypeScript and front-end frameworks like React are also necessary for full-stack roles.


  • Cloud platforms: Expertise in cloud platforms (Azure, AWS, or GCP) and related services is critical for deploying and managing AI solutions.


  • Databases: Knowledge of both relational and NoSQL databases is required.


  • Other technical skills: Experience with containerization (Docker, Kubernetes), version control (Git), and CI/CD pipelines is a major asset.


  • Soft skills: Excellent communication, problem-solving, and collaboration skills are vital for working in interdisciplinary and multicultural teams.




Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.



Required Skill Profession

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