Artificial Intelligence (AI) & Machine Learning (ML
KPI Manufacturing
San Francisco, CA, US
Onsite
2026-06-25
Announced salary
$83k–$100k
Low
$113K
Median
$149K
High
$196K
Market in San Francisco · BLS OEWS 2025
Job description
**Overview**
Join our innovative team as an Artificial Intelligence (AI) \& Machine Learning (ML) Specialist, where you will drive the development and deployment of cutting\-edge AI solutions that transform data into actionable insights. This role offers an exciting opportunity to work at the forefront of technology, leveraging advanced frameworks and tools to solve complex problems across diverse industries. You will collaborate with cross\-functional teams to design, implement, and optimize intelligent systems that enhance business performance and customer experiences. If you are passionate about harnessing the power of AI and ML to shape the future, this is your chance to make a meaningful impact in a dynamic environment.
**Responsibilities**
* Develop, train, and fine\-tune machine learning models using frameworks such as TensorFlow, Spark MLlib, and other popular tools to address real\-world challenges.
* Design and implement scalable data pipelines utilizing ETL processes with Talend, Bash scripting, and Hadoop to prepare large datasets for analysis.
* Apply unsupervised learning techniques to uncover hidden patterns and insights within complex data sets.
* Collaborate with data engineers to optimize database design and manage big data environments on platforms like AWS, Hadoop, and Spark.
* Utilize natural language processing (NLP) methods to build intelligent language models for chatbots, sentiment analysis, or document classification.
* Deploy machine learning models into production environments ensuring robustness, scalability, and security through model deployment best practices.
* Conduct data mining activities using SQL, R, SAS, and Python to extract valuable insights that inform strategic decisions.
* Engage in model training activities involving model evaluation, hyperparameter tuning, and performance monitoring.
* Support quantum engineering initiatives where applicable to explore emerging AI paradigms.
* Use analytics tools such as Looker and V