Palantir Sr Data Engineer

Palantir Sr Data Engineer

eTeam

Manhattan, NY • On-site

$126.10K - $151.40K/yr

Full-time

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Job description

Job Summary:
eTeam is a company seeking a Palantir Sr Data Engineer to design and implement AI/ML models tailored to specific business problems. The role involves collaborating with cross-functional teams to integrate models into production environments and ensuring their continued accuracy and compliance with ethical standards.
Responsibilities:
• Design and implement AIML models tailored to specific business problems preferably Insurance including generative LLM models and traditional ML approaches
• Select appropriate algorithms and architectures based on data characteristics performance requirements and usecase complexity
• Conduct feature engineering hyperparameter tuning and model validation to optimize performance and generalizability
• Strong proficiency in Python TypeScript and ML libraries eg TensorFlow PyTorch scikitlearn
• Evaluate model performance using statistical metrics and realworld testing ensuring robustness and fairness
• Collaborate with crossfunctional teams business product managers to integrate models into production environments
• Monitor maintain and retrain models to ensure continued accuracy relevance and compliance with ethical standards
• Document model development processes for reproducibility and knowledge sharing across teams
• Stay current with advancements in ML algorithms generative architectures eg transformers graph neural networks and tooling eg MLflow Kubeflow Hugging Face and so on
• An added advantage if worked on Palantir Foundry AIP Functions
Qualifications:
Required:
• At least 7 years of experience
• Strong in Gen AI ML Python TypeScript
• Design and implement AIML models tailored to specific business problems preferably Insurance including generative LLM models and traditional ML approaches
• Select appropriate algorithms and architectures based on data characteristics performance requirements and usecase complexity
• Conduct feature engineering hyperparameter tuning and model validation to optimize performance and generalizability
• Strong proficiency in Python TypeScript and ML libraries eg TensorFlow PyTorch scikitlearn
• Evaluate model performance using statistical metrics and realworld testing ensuring robustness and fairness
• Collaborate with crossfunctional teams business product managers to integrate models into production environments
• Monitor maintain and retrain models to ensure continued accuracy relevance and compliance with ethical standards
• Document model development processes for reproducibility and knowledge sharing across teams
• Stay current with advancements in ML algorithms generative architectures eg transformers graph neural networks and tooling eg MLflow Kubeflow Hugging Face and so on
Preferred:
• An added advantage if worked on Palantir Foundry AIP Functions
Company:
eTeam is a staffing agency that also provides payrolling services. Founded in 1999, the company is headquartered in Somerset, USA, with a team of 501-1000 employees. The company is currently Late Stage.


Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Software Engineer?

A: To succeed as a Data Software Engineer, key technical skills include proficiency in programming languages such as Python, Java, or C++, as well as expertise in data structures, algorithms, and software development methodologies like Agile. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Software Engineers often work with cross-functional teams and stakeholders to design, develop, and deploy data-driven solutions. By combining technical expertise with strong soft skills, Data Software Engineers can effectively drive business outcomes, innovate, and adapt to the rapidly evolving landscape of data technology.

Q: What is the career path for a Data Software Engineer?

A: A Data Software Engineer's typical career progression involves starting as a Junior Software Engineer, where they focus on developing and maintaining data-driven software applications, and gradually advancing to roles such as Senior Software Engineer, Technical Lead, or Data Architect, where they oversee large-scale data systems and lead cross-functional teams. Key opportunities for skill development include learning programming languages like Python, SQL, and Java, as well as data science tools like Hadoop, Spark, and machine learning frameworks like TensorFlow and PyTorch. Long-term, Data Software Engineers may pursue leadership roles, such as Director of Engineering or Chief Technology Officer, or transition into related fields like data science, product management, or entrepreneurship.