Data Scientist - Palantir; GenAI MLOps Engineer
Job in
Jersey City, Hudson County, New Jersey, 07390, USA
Listed on 2026-01-12
Listing for:
Inizio Partners Corp
Full Time
position Listed on 2026-01-12
Job specializations:
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Engineer -
Engineering
AI Engineer, Data Engineer
Job Description & How to Apply Below
Job Openings Data Scientist - Palantir (GenAI MLOps Engineer)
About the job Data Scientist - Palantir (GenAI MLOps Engineer)- Job Title:
Data Scientist Palantir (GenAI MLOps Engineer) - Location:
Jersey City, NJ (onsite) - Experience: 15+ years
- NOTE:
- Candidate must be ready to join onsite from day 1 at Jersey City office if selected.
Required Skills and Qualifications:
- Bachelors or Masters degree in Computer Science, Data Engineering, Data Science, or a related field.
- Strong hands‑on experience working with Palantir Foundry and/or Palantir Gotham for data integration, transformation, and analysis.
- Proven experience in MLOps or similar roles involving machine learning and cloud operations.
- Strong knowledge of AWS services (e.g.,
Sage Maker
, Lambda
, EC2
, S3
, Redshift
, Glue
, Kinesis
). - Proficiency in programming languages such as Python
, SQL
, and bash for data manipulation and automation. - Experience with machine learning frameworks and tools like Tensor Flow
, Py Torch ,
Scikit-learn
, MLflow
, and Kubeflow
. - Familiarity with containerization and orchestration technologies such as Docker and Kubernetes
. - Solid understanding of CI/CD pipelines and tools like Jenkins
, Git Lab
, or Git Hub Actions
. - Strong problem‑solving skills with the ability to troubleshoot and debug complex systems.
- Excellent communication skills, both written and verbal, with the ability to present technical concepts clearly.
Preferred Qualifications:
- Advanced degree (Master's or Ph.D.) in a relevant field.
- AWS Certified Solutions Architect or Certified Machine Learning Specialty certification.
- Familiarity with Dev Ops practices and tools.
- Experience with real‑time data streaming and event‑driven architectures
. - Knowledge of big data technologies like Hadoop
, Spark
, and Flink
.
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