We’re looking for a software engineer with a strong foundation in Python and deep experience in Artificial Intelligence and Machine Learning, particularly in the areas of Large Language Models (LLMs) and Computer Vision. The right candidate will have a proven track record of building, testing, and scaling Python-based systems, along with a solid grasp of AI/ML methodologies and their practical applications. <ul><li>Analyze software requirements and evaluate technical solutions to meet functional goals.</li><li>Stay current with emerging research and publicly available models in LLMs, Computer Vision, and multimodal AI.</li><li>Collaborate with peers to assess and refine proposed technical strategies.</li><li>Develop Python-based microservices aligned with architectural designs.</li><li>Conduct testing and integrate services into the broader software ecosystem.</li><li>Maintain thorough documentation of research findings and implementation details.</li><li>Contribute to a collaborative and knowledge-sharing team culture. </li></ul> <ul><li>Eligible for a security clearance.</li><li>2 to 5 years of practical experience in Python software development.</li><li>Bachelor’s degree in Computer Science, Data Science, or a closely related discipline.</li><li>Proficiency with machine learning libraries such as Pandas, NumPy, PyTorch, and spaCy.</li><li>Familiarity with LLM tools and ecosystems like Langchain, LlamaIndex, and providers such as sglang, vLLM, and OpenAI.</li><li>Experience working in environments like Jupyter Notebooks, Google Colab, and visualization tools such as Matplotlib, Plotly, and geoplotlib.</li><li>Understanding of transformer models, embedding techniques, transfer learning, and fine-tuning.</li><li>Solid foundation in statistical analysis and machine learning approaches including clustering, regression, neural networks, and deep learning.</li><li>Strong communication skills, both written and verbal, with the ability to convey technical concepts to stakeholders.</li><li>Willingness to travel occasionally for client engagements. </li></ul> <ul><li>Exposure to Agentic AI frameworks (e.g., langgraph) and concepts like MCP and Retrieval-Augmented Generation (RAG).</li><li>Knowledge of natural language processing techniques such as TF-IDF, Bag of Words, Named Entity Recognition, and Part-of-Speech tagging.</li><li>Experience with distributed computing and data platforms like Spark, Hive, MongoDB, and MapReduce.</li><li>Understanding of modern cloud-native architectures and tools such as Docker, AWS, GCP, Jenkins, and TeamCity.</li><li>Master’s degree in a relevant technical field is a plus.</li></ul>

Apache Spark, Python, Apache Hadoop, Apache Kafka, ETL - Extract Transform Load

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Princeton, NJ
remote
Temporary
68.00 - 80.00 USD / Hourly
We’re looking for a software engineer with a strong foundation in Python and deep experience in Artificial Intelligence and Machine Learning, particularly in the areas of Large Language Models (LLMs) and Computer Vision. The right candidate will have a proven track record of building, testing, and scaling Python-based systems, along with a solid grasp of AI/ML methodologies and their practical applications. <ul><li>Analyze software requirements and evaluate technical solutions to meet functional goals.</li><li>Stay current with emerging research and publicly available models in LLMs, Computer Vision, and multimodal AI.</li><li>Collaborate with peers to assess and refine proposed technical strategies.</li><li>Develop Python-based microservices aligned with architectural designs.</li><li>Conduct testing and integrate services into the broader software ecosystem.</li><li>Maintain thorough documentation of research findings and implementation details.</li><li>Contribute to a collaborative and knowledge-sharing team culture. </li></ul> <ul><li>Eligible for a security clearance.</li><li>2 to 5 years of practical experience in Python software development.</li><li>Bachelor’s degree in Computer Science, Data Science, or a closely related discipline.</li><li>Proficiency with machine learning libraries such as Pandas, NumPy, PyTorch, and spaCy.</li><li>Familiarity with LLM tools and ecosystems like Langchain, LlamaIndex, and providers such as sglang, vLLM, and OpenAI.</li><li>Experience working in environments like Jupyter Notebooks, Google Colab, and visualization tools such as Matplotlib, Plotly, and geoplotlib.</li><li>Understanding of transformer models, embedding techniques, transfer learning, and fine-tuning.</li><li>Solid foundation in statistical analysis and machine learning approaches including clustering, regression, neural networks, and deep learning.</li><li>Strong communication skills, both written and verbal, with the ability to convey technical concepts to stakeholders.</li><li>Willingness to travel occasionally for client engagements. </li></ul> <ul><li>Exposure to Agentic AI frameworks (e.g., langgraph) and concepts like MCP and Retrieval-Augmented Generation (RAG).</li><li>Knowledge of natural language processing techniques such as TF-IDF, Bag of Words, Named Entity Recognition, and Part-of-Speech tagging.</li><li>Experience with distributed computing and data platforms like Spark, Hive, MongoDB, and MapReduce.</li><li>Understanding of modern cloud-native architectures and tools such as Docker, AWS, GCP, Jenkins, and TeamCity.</li><li>Master’s degree in a relevant technical field is a plus.</li></ul>
2025-10-28T18:18:42Z