AI Data Scientist - Full-time | Remote (U.S.-based) | Entry Level

Insilicom; United States; Remote; USD 100,000 - 720,000; Full time

Job summary

A leading company, Insilicom, is looking for an innovative AI Data Scientist to enhance biomedical research using advanced AI techniques. The role requires expertise in machine learning and natural language processing with a focus on biomedical data analysis. Ideal candidates will hold a Master's or Ph.D. in relevant fields, possess strong programming skills, and be ready to work in a collaborative environment.

Qualifications

• Strong proficiency in Python and deep learning frameworks required.
• Experience with neural networks and NLP techniques is crucial.
• Hands-on experience in deploying machine learning models is preferred.

Responsibilities

• Develop and implement advanced deep learning and NLP models.
• Lead end-to-end model development, ensuring scalable performance.
• Collaborate with teams to integrate AI models into production.

Skills

Machine Learning

Deep Learning

Natural Language Processing

Python

Education

Master's or Ph.D. in relevant field

Tools

TensorFlow

PyTorch

Job description

AI Data Scientist - Full-time | Remote (U.S.-based) | Entry Level

AI Data Scientist - Full-time | Remote (U.S.-based) | Entry Level

1 week ago Be among the first 25 applicants

Company Overview: Insilicom provides AI-driven solutions to harness Big Data and accelerate research and development efforts in both industry and academia. We specialize in document retrieval, information extraction, knowledge management, and knowledge discovery using knowledge graph-based AI algorithms.

Position Summary: We are seeking an innovative AI Data Scientist to join our team in advancing biomedical research through artificial intelligence. This role combines expertise in machine learning, deep learning, and large language models (LLMs) with a focus on biomedical data analysis and natural language processing.

Work Authorization: Must be legally authorized to work in the United States (including OPT, H-1B, or other valid work authorizations)

Key Responsibilities:

●Develop and implement advanced deep learning and NLP models for biomedical data analysis.

●Design, optimize, and fine-tune LLMs (e.g., GPT-4, Claude, or similar models) for entity recognition, classification, relation extraction, and text generation.

●Lead end-to-end model development, from data preprocessing to production deployment, ensuring scalable and efficient performance.

●Utilize neural network architectures (transformers, RNNs, CNNs, etc.) for various machine learning tasks.

●Engineer and optimize prompting techniques for improving LLM performance in knowledge discovery and information retrieval.

●Collaborate with cross-functional teams to integrate AI models into production pipelines.

●Conduct thorough model evaluation, hyperparameter tuning, and performance optimization.

●Maintain well-documented, modular, and reusable Python code and AI model repositories.

●Stay current with cutting-edge research in AI, machine learning, and NLP, and apply best practices.

Required Qualifications:

●Master's or Ph.D. in Computer Science, Statistics, Computational Biology, Bioinformatics, Physics, or related fields.

●Strong proficiency in Python (NumPy, Pandas, TensorFlow, PyTorch, Hugging Face Transformers).

●Experience with Linux OS, shell scripting, and version control (Git).

○Neural networks and deep learning architectures (e.g., transformers, LSTMs, CNNs).

○Natural Language Processing (NLP) and information retrieval techniques.

○LLM prompt engineering and optimization (e.g., GPT-4, Claude).

○Large-scale data processing, training, and fine-tuning models.

●Proven ability to develop, optimize, and deploy machine learning models in production environments.

●Strong analytical, problem-solving, and collaborative skills.

Preferred Qualifications:

●Hands-on experience with fine-tuning transformer-based architectures (e.g., BERT, T5, LLaMA).

●Familiarity with cloud platforms (AWS, GCP, Azure) for AI model deployment.

●Advanced knowledge of feature engineering, hyperparameter tuning, and model optimization.

●Published research or industry experience in ML/AI, NLP, or LLMs.

●Strong communication skills with the ability to explain complex AI models to non-technical stakeholders.

Application Requirements:

1.Resume/CV (PDF format)

2.Responses to the following questions in your LinkedIn application:

○Educational background confirmation

○Technical expertise verification

○Machine learning knowledge assessment

Application Process: Rolling applications with priority consideration for early submissions. Candidates are encouraged to apply promptly, as interviews will begin immediately.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

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