[xrecnet] Data scientist with strong Python at Mclean, VA Contract to hire Day1 onsite

Data scientist role  

Mclean, VA

Contract to hire

Day1 onsite

 

Local talents will be preferred, this is Day- 1 onsite role.

 

 

Pls share profiles for the mentioned onsite demands:

 

Required skills	Ratings Out of 5	# of years used		Candidate writeup (must be detailed filled by applicant)
Exp as Data scientist
Exp in working with Python
Exp in working with machine learning technologies.
Java-based applications using Spring Framework and microservices architecture.
Exp in Tokenization
Understanding of how language models like GPT work
Java programming (Good to have)
Work Location (with City, State & Zip Code)			Mclean, Virginia
Client interview required for selection (Yes/No)			Yes
No. of Positions			01
Job Title/Role			Data scientist
Experience level required (Years)			9+ Yrs.
Detailed Job Description			Over 5 years of experience with a strong experience working with Python and machine learning technologies. Design, develop, and maintain Java-based applications using Spring Framework and microservices architecture. Need to have a deep understanding of how language models like GPT work, including their architecture, training methodology, and capabilities. Need to have good knowledge of Tokenization: Tokenization is the process of breaking down text into smaller units (tokens) for analysis. Should be familiar with different tokenization techniques and their implications for prompt engineering. Need to have good understanding of various Text Generation Techniques, including techniques for controlling the output of language models through prompts, prefixes, and conditioning. Should have expertise in designing effective prompts tailored to specific tasks and objectives, since prompt engineering involves crafting input prompts or instructions to guide the language model's output. Strong Fine-tuning Strategies skills, which involves adapting pre-trained language models to specific tasks or domains by providing task-specific data and fine-tuning parameters. Should know how to effectively fine-tune models for optimal performance. Should be familiar with evaluation metrics commonly used to assess the quality and performance of text generation tasks, such as perplexity, BLEU score, ROUGE score, and human evaluation. Should be familiar with Bias Mitigation, since potential biases present in language models.  Should understand techniques for mitigating biases in model outputs, such as debiasing strategies and fairness-aware training. Should have skills in interpreting and analyzing model outputs to understand how prompts influence the generated text and identify patterns or biases in the model's behavior. Troubleshoot and debug issues, providing timely resolution to ensure smooth operation of applications. Stay up-to-date with the latest industry trends and best practices in Java, Python, and machine learning.

 

 

 

 

 

 

Regards

Pavan

VDart Inc

Ph: (470) 251-2584 Ext:1866

Email: Pavankumar.s@vdartinc.com

Website: https://vdart.com

 

 

 

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