Mindlance
Job Title
Role:
AI/ML Engineer
Location:
Washington, DC
Duration:
5 Months
Hybrid Onsite:
4 days per week from Day 1, with a full transition to 100% onsite anticipated soon.
Job Description We are seeking a skilled AI/ML Engineer to design, develop, and deploy machine learning models and AI-driven solutions. The ideal candidate will work with large datasets, build predictive and generative models, and integrate them into scalable production applications.
Responsibilities
Design, develop, and deploy machine learning and AI models for real‑world use cases.
Work with large datasets for data preprocessing, feature engineering, and model optimization.
Demonstrate strong proficiency in
Python
and ML frameworks such as
PyTorch, TensorFlow, and scikit‑learn .
Develop and fine‑tune
Large Language Models (LLMs)
and implement traditional ML algorithms.
Utilize cloud platforms ( AWS, GCP, Azure ) for model training, deployment, and monitoring.
Apply containerization tools like
Docker
and
Kubernetes
for scalable deployment.
Collaborate with cross‑functional teams to integrate ML solutions into enterprise systems.
Stay current with emerging
AI/ML technologies , including
GPT‑based agents and generative AI tools .
EEO Statement Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
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AI/ML Engineer
Location:
Washington, DC
Duration:
5 Months
Hybrid Onsite:
4 days per week from Day 1, with a full transition to 100% onsite anticipated soon.
Job Description We are seeking a skilled AI/ML Engineer to design, develop, and deploy machine learning models and AI-driven solutions. The ideal candidate will work with large datasets, build predictive and generative models, and integrate them into scalable production applications.
Responsibilities
Design, develop, and deploy machine learning and AI models for real‑world use cases.
Work with large datasets for data preprocessing, feature engineering, and model optimization.
Demonstrate strong proficiency in
Python
and ML frameworks such as
PyTorch, TensorFlow, and scikit‑learn .
Develop and fine‑tune
Large Language Models (LLMs)
and implement traditional ML algorithms.
Utilize cloud platforms ( AWS, GCP, Azure ) for model training, deployment, and monitoring.
Apply containerization tools like
Docker
and
Kubernetes
for scalable deployment.
Collaborate with cross‑functional teams to integrate ML solutions into enterprise systems.
Stay current with emerging
AI/ML technologies , including
GPT‑based agents and generative AI tools .
EEO Statement Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
#J-18808-Ljbffr