AI - ML ( Machine Learning) Developer from Quadrant Inc
Arlington, VA
About the Job
Job ID: 25-04606
AI/ML Developer
Arlington, VA (Remote)
Pay From: $65 per hour
MUST:
Experienced AI/ML Developer
CBP Public Trust
3+ years of hands-on experience in implementation and development of Generative AI related solutions, with a strong track record of building and deploying production-grade solutions.
Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar, with expertise in developing and training deep generative models (GANs, VAEs, etc.).
Strong programming skills in Python and experience with software development best practices, version control systems (e.g., Git), and containerization technologies (e.g., Docker).
Experience developing RAG (Retrieval Augmented Generation) based applications. Experience with the various advanced RAG methodologies.
Experience with Natural Language Processing (NLP), including architecture and functioning of language models like BERT, GPT, or transformers; text preprocessing performing text normalization, tokenization, and lemmatization.
Familiarity with machine learning algorithms, neural networks, and deep learning frameworks, including understanding architectures like transformers.
Solid understanding of machine learning fundamentals, optimization techniques, and mathematical concepts underlying generative AI algorithms.
Excellent problem-solving abilities, analytical thinking, and attention to detail, with a passion for pushing the boundaries of what's possible with generative AI.
Effective communication skills and ability to collaborate with interdisciplinary teams in a fast-paced, dynamic environment.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
DUTIES:
Application Development: Write python codes to develop application modules and implement Generative AI solutions.
Algorithm Design & Optimization: Design and optimize generative AI algorithms and models tailored to specific use cases and applications, ensuring scalability, efficiency, and effectiveness.
Model Training & Evaluation: Develop and implement robust training pipelines for generative AI models, utilizing large-scale datasets and advanced optimization techniques. Evaluate model performance using relevant metrics and benchmarks.
Deployment & Integration: Collaborate with cross-functional teams to deploy generative AI solutions into production environments, integrating them seamlessly with existing systems and workflows.
Create and manage Vector Store databases utilizing various embedding methods.
Performance Optimization: Identify performance bottlenecks and optimize generative AI algorithms and systems for improved speed, scalability, and resource efficiency.
Collaboration & Knowledge Sharing: Work closely with developers and other stakeholders to foster a collaborative environment for sharing knowledge, best practices, and insights in generative AI.
Quadrant is an affirmative action/equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, status as a protected veteran, or status as an individual with a disability. Healthcare benefits are offered to all eligible employees according to compliance mandated by the Affordable Care Act .
AI/ML Developer
Arlington, VA (Remote)
Pay From: $65 per hour
MUST:
Experienced AI/ML Developer
CBP Public Trust
3+ years of hands-on experience in implementation and development of Generative AI related solutions, with a strong track record of building and deploying production-grade solutions.
Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar, with expertise in developing and training deep generative models (GANs, VAEs, etc.).
Strong programming skills in Python and experience with software development best practices, version control systems (e.g., Git), and containerization technologies (e.g., Docker).
Experience developing RAG (Retrieval Augmented Generation) based applications. Experience with the various advanced RAG methodologies.
Experience with Natural Language Processing (NLP), including architecture and functioning of language models like BERT, GPT, or transformers; text preprocessing performing text normalization, tokenization, and lemmatization.
Familiarity with machine learning algorithms, neural networks, and deep learning frameworks, including understanding architectures like transformers.
Solid understanding of machine learning fundamentals, optimization techniques, and mathematical concepts underlying generative AI algorithms.
Excellent problem-solving abilities, analytical thinking, and attention to detail, with a passion for pushing the boundaries of what's possible with generative AI.
Effective communication skills and ability to collaborate with interdisciplinary teams in a fast-paced, dynamic environment.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
DUTIES:
Application Development: Write python codes to develop application modules and implement Generative AI solutions.
Algorithm Design & Optimization: Design and optimize generative AI algorithms and models tailored to specific use cases and applications, ensuring scalability, efficiency, and effectiveness.
Model Training & Evaluation: Develop and implement robust training pipelines for generative AI models, utilizing large-scale datasets and advanced optimization techniques. Evaluate model performance using relevant metrics and benchmarks.
Deployment & Integration: Collaborate with cross-functional teams to deploy generative AI solutions into production environments, integrating them seamlessly with existing systems and workflows.
Create and manage Vector Store databases utilizing various embedding methods.
Performance Optimization: Identify performance bottlenecks and optimize generative AI algorithms and systems for improved speed, scalability, and resource efficiency.
Collaboration & Knowledge Sharing: Work closely with developers and other stakeholders to foster a collaborative environment for sharing knowledge, best practices, and insights in generative AI.