Trillion Technology Solutions Inc.
JR AI/ML Engineer
Trillion Technology Solutions Inc., Reston, Virginia, United States, 22090
We are seeking a highly skilled AI/ML engineer to join our team for a DoD DISA contract. The ideal candidate will have experience developing and implementing AI/ML solutions and a strong background in data analytics, cloud technologies, and data governance. This role requires a deep understanding of AI/ML algorithms, data preparation, and model deployment in a secure, federal environment.
Technical Skills:Proficiency in Python:
A strong command of Python programming is essential for working with language models and implementing AI solutions.Understanding of C/C++:
Familiarity with reading C/C++ code can be valuable, especially when dealing with low-level optimizations or interfacing with existing libraries.Machine Learning Workflows:
Experience in designing, training, evaluating, and deploying machine learning models is crucial. This includes feature selection, dataset curation, and algorithm selection.Fine-Tuning Large Language Models:
Expertise in fine-tuning pre-trained language models (such as GPT-3, BERT, or similar) to specific tasks or domains.Familiar with PySpark and data processing libraries, machine learning frameworks (like Tensorflow, Keras or PyTorch), and other machine learning libraries.Familiar with Machine Learning life cycle, with knowledge of feature stores, MLflow, model registries, model deployment, model serving, and model monitoring.Educational Background:Bachelor's Degree or Higher:
A degree in
Data Science ,
Computer Science , or a related field provides a solid foundation. A master's or PhD is advantageous but not always necessary.Language Proficiency:Complete Fluency in English:
Effective communication is essential for collaborating with teams, documenting research, and explaining complex concepts.Experience:Industry Experience:
Look for candidates with at least
2 years of experience
in data analysis, data science, or related roles.Hands-On Work with Language Models:
Prior work involving large language models, whether in research or practical applications, demonstrates expertise.Adaptability and Creativity:Problem-Solving Skills:
Generative AI often requires creative solutions to novel challenges. Seek candidates who can think outside the box.Ability to Adapt to New Models:
The field evolves rapidly, so an openness to learning and adapting to new language models is crucial.Domain Knowledge:Understanding of NLP and Text Generation:
Familiarity with natural language processing (NLP) concepts and text generation techniques is beneficial.Specific Domain Expertise:
Depending on your organization's focus (e.g., healthcare, finance, marketing), consider candidates with relevant domain knowledge.Collaboration and Teamwork:Collaborative Attitude:
Generative AI projects often involve interdisciplinary teams. Look for candidates who can work effectively with others.Key Responsibilities:
Develop and implement AI/ML models to support data-driven decision-making.Collaborate with data scientists, data engineers, and other stakeholders to design and deploy scalable AI/ML solutions.Ensure data quality, integrity, and security in all AI/ML projects.Conduct research and stay updated on the latest AI/ML trends and technologies.Provide technical leadership and mentorship to junior team members.Work closely with the Chief Data Officer to align AI/ML initiatives with organizational goals.Develop and maintain documentation for AI/ML models and processes.Ensure compliance with federal regulations and standards.Trillion is an equal opportunity employer. Applicants are considered for positions without regard to race, religion, gender, native origin, age, disability, or any other category protected by applicable federal, state, or local law.
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Technical Skills:Proficiency in Python:
A strong command of Python programming is essential for working with language models and implementing AI solutions.Understanding of C/C++:
Familiarity with reading C/C++ code can be valuable, especially when dealing with low-level optimizations or interfacing with existing libraries.Machine Learning Workflows:
Experience in designing, training, evaluating, and deploying machine learning models is crucial. This includes feature selection, dataset curation, and algorithm selection.Fine-Tuning Large Language Models:
Expertise in fine-tuning pre-trained language models (such as GPT-3, BERT, or similar) to specific tasks or domains.Familiar with PySpark and data processing libraries, machine learning frameworks (like Tensorflow, Keras or PyTorch), and other machine learning libraries.Familiar with Machine Learning life cycle, with knowledge of feature stores, MLflow, model registries, model deployment, model serving, and model monitoring.Educational Background:Bachelor's Degree or Higher:
A degree in
Data Science ,
Computer Science , or a related field provides a solid foundation. A master's or PhD is advantageous but not always necessary.Language Proficiency:Complete Fluency in English:
Effective communication is essential for collaborating with teams, documenting research, and explaining complex concepts.Experience:Industry Experience:
Look for candidates with at least
2 years of experience
in data analysis, data science, or related roles.Hands-On Work with Language Models:
Prior work involving large language models, whether in research or practical applications, demonstrates expertise.Adaptability and Creativity:Problem-Solving Skills:
Generative AI often requires creative solutions to novel challenges. Seek candidates who can think outside the box.Ability to Adapt to New Models:
The field evolves rapidly, so an openness to learning and adapting to new language models is crucial.Domain Knowledge:Understanding of NLP and Text Generation:
Familiarity with natural language processing (NLP) concepts and text generation techniques is beneficial.Specific Domain Expertise:
Depending on your organization's focus (e.g., healthcare, finance, marketing), consider candidates with relevant domain knowledge.Collaboration and Teamwork:Collaborative Attitude:
Generative AI projects often involve interdisciplinary teams. Look for candidates who can work effectively with others.Key Responsibilities:
Develop and implement AI/ML models to support data-driven decision-making.Collaborate with data scientists, data engineers, and other stakeholders to design and deploy scalable AI/ML solutions.Ensure data quality, integrity, and security in all AI/ML projects.Conduct research and stay updated on the latest AI/ML trends and technologies.Provide technical leadership and mentorship to junior team members.Work closely with the Chief Data Officer to align AI/ML initiatives with organizational goals.Develop and maintain documentation for AI/ML models and processes.Ensure compliance with federal regulations and standards.Trillion is an equal opportunity employer. Applicants are considered for positions without regard to race, religion, gender, native origin, age, disability, or any other category protected by applicable federal, state, or local law.
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