Overview
Remote
Depends on Experience
Contract - W2
Contract - Independent
Skills
Machine Learning
TensorFlow
LSTMs
Diffusion Models
NODEs
NumPy
Architect
Job Details
What you ll bring:
Minimum Qualifications
- Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related field; or 2+ years of experience in a related, professional IT/analytics position.
- Minimum of 5 years of industry experience in developing, deploying, and maintaining AI or ML systems. Up to two years of industry experience may be
- substituted with an AI-centered Master s/Ph.D. or AI Engineering certifications.
Preferred Qualifications
- At least 8 years of experience in developing deep learning models using
- TensorFlow, PyTorch, MLX, JAX, or other modern deep learning frameworks.
- Previous experience with older libraries like Theano, or Caffe is also accepted. (May supplement with graduate level education or research experience).
- Experience with design patterns and microservices architecture, including at least 5 years with container orchestration in a production environment.
- Knowledge of and experience in implementing ethical AI practices, with at least 5 years spent working on projects that require explainable AI, fairness, and bias mitigation.
- At least 8 years of experience with demonstrated mastery over a wide range of
- AI technologies. A proven thought leader with published research and artifacts that advance the field of AI. Possess a proven track record of leading large-scale AI projects.
- Minimum of 5 years of experience in successfully producing AI models, including constructing scalable data pipelines and establishing robust monitoring systems.
- Minimum of 5 years demonstrating excellent communication skills through the ability to articulate complex AI solutions to non-technical stakeholders, coupled with a history of collaborative work and mentorship in Agile-like environments.
- Expertise in developing deep learning architectures such as CNNs, transformers, GANs, LSTMs, GNNs, Autoencoders, Diffusion Models, and Neural Ordinary
- Differential Equations (NODEs).
- Mastery over a wide range of prompt engineering techniques, tools, and libraries to innovate in the field of prompt engineering to solve complex problems.
- Possess a proven track record of leading large-scale prompt engineering
- projects, optimizing prompt engineering pipelines.
- Mastery at debugging AI systems and enhancing performance through hyperparameter tuning and similar techniques.
- Proven experience in productionizing models by constructing scalable data pipelines, low-latency services, and robust monitoring.
- Knowledgeable about software design patterns, microservices, and distributed computing, container orchestration, and other relevant architectures.
- Excellent software engineering skills as well as mastery of building secure, stable software systems at scale.
- Proven experience developing and optimizing ML solutions using languages like
- Python and libraries such as NumPy, Pandas, Matplotlib, and scikit-learn.
- Familiarity with working with traditional ML lifecycles.
- Solid knowledge of ethical AI practices, including explainable AI, fairness, and mitigation of bias/hallucinations.
- Excellent communication, collaboration, mentorship, and team leadership skills.
- Skilled at leading Agile-like teams and environments.
- Ability to articulate the technical details and tradeoffs of AI solutions to executives and other non-technical stakeholders in a clear, concise, and compelling manner.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.