Who We Are
Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to customers.
Job Description
Job Title : Senior AI & Data Research Scientist – Emerging Technologies
Job Type : W2
Experience : 7 - 20 years
Location : Mountain View, California
Required Skills And Experience - Corporate lab setting with a proven track record of cross functional collaboration and achievements experience
- Key components of IoT, edge, distributed cloud architecture with emphasis on connected systems – 3 years
- Experience of proof-of-concept (PoC) prototyping for connected cars and IoT systems - 3 years
- Experienced with prototyping and cloud bulk data injestion techniques (e.g. AWS, Spark, Kaftka)- 2 years
- Programming experience with Python, Rust and embedded systems (e.g. NVIDIA Jetson, Arduino, etc) - 2 years
- Working experience and knowledge of connect car architecture and vehicle compute requirements - 2 years
- Broad knowledge of Computer Systems, Software engineering and Embedded Systems
- Experience working and communicating in multicultural and multinational companies - 2 years
- Hands on experience in R&D with proven credential in patents and publications - 5 year
- Strong familiarity with end to end data services/domains and technologies.
- Data Ingest (ETL, ELT, File, Streaming, Queue, etc.)
- Data integration (Quality, cleansing, labelling, API, etc)
- Data Processing
- Data Access
- Data Analytics (familiar with different tools)
- Databases (unstructured and structured – SQL, NoSQL, Vector, RDMBS, etc.)
- Data Storage technology (SSD, HDD, etc)
- Memory/Cache
- PoC and Benchmarking experience in AI or data infrastructure
- Strong research interest in data areas where data is the foundation for AI computer
- Research experience with data infrastructure, platform development, IoT, etc - 3 years
- Experience with advanced data platform, distributed cloud systems & architecture including data management, data ingestion, data analytics, data processing, data observability for infrastructure, data normalization, clustering, logs, tools, monitoring, etc. - 3 years
- Hands-on prototyping and programming knowledge (e.g. Python, SQL/NoSQL, Kafka, Spark, etc). – 3 year
- Managed research projects, e.g., planning, reporting, and managing time / team / outside collaborators – 3 year
- Well-developed interpersonal and communication skills, including ability to respond professionally in all types of situation.
Responsibilities - Define research goals & tasks for AI and/or data technology.
- Work with university researchers on emergent AI and data technologies and algorithms.
- Research and develop data platforms (open source, commercial) where this platform can be used widely across multiple business services including battery, supply chain, marketing, mobility, chatgpt for support, etc.
- Innovate and develop new data capabilities.
- Generate patents and publications.
- Lead discussions of multiple number of products/applications using emerging data and AI technologies.
- Research and develop new capabilities within the data domains (data ingest, data integration, data labeling, data cleansing, data processing, data and AI analytics, data management).
- Develop innovative ideas and solutions for AI and data domains that deliver
- Better performance and Scalability
- Lower cost and reduce latency
- High Availability and Redundancy
- Observability and Reliability
- Encryption, Security, etc.
- Conduct PoC and benchmarks data services/capabilities to compare performance, costs and other criteria.
- Establish research collaborations with leading experts in universities and industry consortiums
- Mentoring and training junior researchers in group/department wide
- Technology transfer ITL research to advanced development or valuable business contribution to the company
- Obtain patents and publish research in prestigious journals and conferences
- Regularly champion research and present/influence to VP and GVP level and show AI or data technology expertise.
- Evangelize the importance of AI, generative AI, AI platform and create vision and roadmap.
Qualification
- PhD in Engineering (e.g. Computer Science, Data Science, Information/Data Management, Math, Statistics, Information Theory, etc) or related field
