Senior Applied Scientist – Multimodal LLMs Position Available In Montgomery, Pennsylvania

Job Description:

Samsara (

NYSE:

IOT) is the pioneer of the Connected Operations™Cloud, which is a platform that enables organizations that dependon physical operations to harness Internet of Things (IoT) data todevelop actionable insights and improve their operations. AtSamsara, we are helping improve the safety, efficiency andsustainability of the physical operations that power our globaleconomy. Representing more than 40% of global GDP, these industriesare the infrastructure of our planet, including agriculture,construction, field services, transportation, and manufacturing —and we are excited to help digitally transform their operations atscale. Working at Samsara means you’ll help define the future ofphysical operations and be on a team that’s shaping an excitingarray of product solutions, including Video-Based Safety, VehicleTelematics, Apps and Driver Workflows, Equipment Monitoring, andSite Visibility. As part of a recently public company, you’ll havethe autonomy and support to make an impact as we build for the longterm.

About the role:

The Samsara ML Science team applies anddevelops cutting-edge technologies that increase the safety,efficiency and sustainability of physical operations. We leveragepetabyte scale data from our huge variety of sensors, includingvideo, GPS, IMU, audio, CAN, and more. As a Senior AppliedScientist specializing in multimodal modeling, you will train bothpowerful and cost-efficient models that leverage these diversemodalities. You will work closely with various engineering teamsacross ML and firmware, as well as cross functional partners. Thisis a remote position open to candidates based in the United States.

You should apply if:

• You want to impact the industries that runour world: The software, firmware, and hardware you build willresult in real-world impact—helping to keep the lights on, get foodinto grocery stores, and most importantly, ensure workers returnhome safely.
• You want to build for scale: With over 2.3 millionIoT devices deployed to our global customers, you will work on arange of new and mature technologies driving scalable innovationfor customers across industries driving the worlds physicaloperations.
• You are a life-long learner: We have ambitious goals.

Every Samsarian has a growth mindset as we work with a wide rangeof technologies, challenges, and customers that push us to learn onthe go.

• You believe customers are more than a number: Samsaraengineers enjoy a rare closeness to the end user and you will havethe opportunity to participate in customer interviews, collaboratewith customer success and product managers, and use metrics toensure our work is translating into better customer outcomes.
• Youare a team player: Working on our Samsara Engineering teamsrequires a mix of independent effort and collaboration. Motivatedby our mission, we’re all racing toward our connected operationsvision, and we intend to win—together. In this role, you will:
• Build and improve ML models, including retraining and optimizingopen-source models to solve Samsara-specific problems
• Work withpetabyte-scale data from Samsara’s cameras and diverse sensors todevelop new multimodal models
• Research and apply cutting-edgetechnologies from the latest industry and academic research
• Collaborate with cross-functional teams to develop innovative AIproducts from scratch
• Champion, role model, and embed Samsara’scultural principles (Focus on Customer Success, Build for the LongTerm, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as wescale globally and across new offices Minimum requirements for therole:
• 5 years experience as an Applied Scientist, MachineLearning Engineer, or similar role
• BS or MS in Computer Scienceor another quantitative field
• Strong proficiency in one or morecommon languages (e.g., Python, Java, C++, Golang)
• Proficiencywith common ML tools and frameworks (e.g., PyTorch, TensorFlow,Spark)
• Proficiency in pulling your own data via SQL, Spark, or asimilar data-querying language
• Experience iteratively refiningmodels using customer feedback loops An ideal candidate also has:
• Ph.D. in Computer Science or quantitative discipline (e.g., AppliedMath, Physics, Statistics)
• Experience working with large datasetsusing distributed computing (e.g., Spark)
• Expertise withdistributed model training of LLMs / MLLMs
• Experience modelingwith a variety of data types including sensor data
• Experienceleading a small cross-functional team to deliver new MLexperiences