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🤖ML Engineer

Senior, ML Engineer

Torc Robotics · Ann Arbor, MI, Remote - US
// classified as
ML Engineer (Productionizing models, serving, MLOps.)
posted
2d ago
location
Ann Arbor, MI, Remote - US
languages
python
tools
aws, databricks, dynamodb
> stack
pythonawsdatabricksdynamodbmlflows3sparkterraformpandaspytorch
> education
masters
> description
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 2">About the Company</span></span></strong><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559738&quot;:220,&quot;335559739&quot;:100,&quot;335559740&quot;:240}">&nbsp;</span></p> <p><span data-contrast="none">At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p> <p><span data-contrast="none">Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p> <p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 2">Meet The Team</span></span></strong><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559738&quot;:220,&quot;335559739&quot;:100,&quot;335559740&quot;:240}">&nbsp;</span></p> <p><span data-contrast="none">Torc is marching toward its AV 3.0 strategy, where end-to-end Vision-Language-Action (VLA) models perceive, reason, and act directly from sensor data. High-quality, semantically rich training data is the single biggest lever for that strategy, and this team owns it.</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p> <p><span data-contrast="none">Sitting within Offline Perception, this team turns petabytes of logged multi-modal fleet data (images, kinematics) into VLM/VLA-ready datasets: geometric annotations, scenario-level semantic descriptions, action- and trajectory-grounded labels, and reasoning traces that explain why a maneuver was taken. We run a continuous data flywheel — mine long-tail and failure cases, auto-label at scale, validate quality, and feed curated datasets directly into Torc’s end-to-end VLM/VLA model development. You will own the dataset layer that those models learn from.</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p> <p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 2">What </span><span data-ccp-parastyle="heading 2">You’ll</span><span data-ccp-parastyle="heading 2"> Do</span></span></strong><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559738&quot;:220,&quot;335559739&quot;:100,&quot;335559740&quot;:240}">&nbsp;</span></p> <ul> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Own the offline dataset pipeline</span></strong><span data-contrast="none"> — design, implement, test, and deploy Cloud-based pipelines that convert logged multi-sensor data into VLM/VLA training datasets, spanning geometric labels (3D/2D detection, tracking, segmentation, depth) through semantic, scenario-level, and action/trajectory-grounded annotations.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Build VLM-assisted auto-labeling</span></strong><span data-contrast="none"> — develop open-vocabulary detection, dense captioning, semantic enrichment, and scene/scenario description generation that move beyond closed-set bounding boxes, using foundation models to scale annotation and cut manual labeling cost.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Generate reasoning-grounded labels</span></strong><span data-contrast="none"> — produce language-grounded reasoning and chain-of-causation style annotations, temporally aligned to ego-motion and trajectories, to support VLA training and explainable driving behavior.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Mine and curate the long tail</span></strong><span data-contrast="none"> — surface rare, difficult, and high-uncertainty scenarios, and build curated datasets that measurably improve downstream VLM/VLA model metrics rather than simply adding volume.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Close the data flywheel</span></strong><span data-contrast="none"> — define dataset schemas, quality metrics, and validation; track auto-labeling quality against model requirements; route model failures back into re-labeling and retraining loops.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Partner with the end-to-end model team</span></strong><span data-contrast="none"> — co-define dataset specifications with VLM/VLA model developers, own the quality bar and delivery cadence, and operationalize a continuous dataset delivery loop into their training pipelines.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Scale on cloud infrastructure</span></strong><span data-contrast="none"> — build distributed, reproducible pipelines using columnar data formats and distributed compute, with disciplined software practices, version control, and documentation.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Lead and mentor</span></strong><span data-contrast="none"> — serve as project lead, guide less-experienced engineers, run design reviews, set coding and annotation standards, and drive alignment across team interfaces to the rest of the organization.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="none">Stay current</span></strong><span data-contrast="none"> — track the latest advances in multimodal models, auto-labeling, and end-to-end autonomous driving, and translate relevant research into production data systems.</span><span data-ccp-props="{&quot;134233279&quot;:false,&quot;201341983&quot;:0,&quot;335559739&quot;:60,&quot;335559740&quot;:240}">&nbsp;</span></li> </ul> <p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 2">What </span><span data-ccp-parastyle="heading 2">You’ll</span><span data-ccp-parastyle="heading 2"> Need to Succeed:</span></span></strong><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559738&quot;:220,&quot;335559739&quot;:100,&quot;335559740&quot;:240}">&nbsp;</span></p> <ul> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="10" data-aria-level="1"><strong><span data-contrast="none">Considered highly skilled and proficient in discipline</span></strong><span data-contrast="none">; conducts complex, important work under minimal supervision and with wide latitude for independent judgment.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="10" data-aria-level="1"><strong><span data-contrast="none">Scope of Influence:</span></strong><span data-contrast="none"> Expected to drive alignment across team interfaces to the rest of the organization. Designs, maintains, and owns team technical solutions and drives consensus. Mentors and guides engineers within the group.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="10" data-aria-level="1">Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering, or related technical field plus competences typically acquired through 6+ years of experience; OR Master’s Degree in a related technical field plus competences typically acquired through 3+ years of experience.<span data-ccp-props="{&quot;134233279&quot;:false,&quot;201341983&quot;:0,&quot;335559739&quot;:60,&quot;335559740&quot;:240}">&nbsp;</span></li> </ul> <p><strong><span data-contrast="none">Required Qualifications </span></strong><strong><em><span data-contrast="none">(some combination of the following skills):</span></em></strong><span data-ccp-props="{&quot;335559738&quot;:80,&quot;335559739&quot;:80}">&nbsp;</span></p> <ul> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="14" data-aria-level="1"><strong><span data-contrast="none">Computer Vision &amp; Deep Learning</span></strong><span data-contrast="none"> — model training and at least two of: 2D/3D Object Detection, Tracking, Sensor Fusion, Semantic Segmentation, BEV, Depth Estimation.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="14" data-aria-level="1"><strong><span data-contrast="none">Multimodal / VLM experience</span></strong><span data-contrast="none"> — hands-on work with vision-language models, open-vocabulary or zero-shot recognition, dense captioning, or semantic embeddings / search applied to perception data.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="14" data-aria-level="1"><strong><span data-contrast="none">Model Data Curation</span></strong><span data-contrast="none"> — building targeted datasets that measurably improve downstream model performance; large-scale Parquet data processing (Databricks, Daft, Pandas, etc.).</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="14" data-aria-level="1"><strong><span data-contrast="none">Distributed ML &amp; data frameworks</span></strong><span data-contrast="none"> — PyTorch, Lightning, Ray, Spark, or equivalent for training and large-scale data processing.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="14" data-aria-level="1"><strong><span data-contrast="none">Scaled MLOps &amp; Tooling</span></strong><span data-contrast="none"> — experiment tracking, model registry, MLflow / Weights &amp; Biases, and ML metrics, evaluation, and quality.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="14" data-aria-level="1"><strong><span data-contrast="none">Development Tools &amp; Eco-System (at scale)</span></strong><span data-contrast="none"> — strong Python software development, VDI and cloud-based development environments, CI systems (GitHub Actions), and Docker.</span><span data-ccp-props="{&quot;134233279&quot;:false,&quot;201341983&quot;:0,&quot;335559739&quot;:60,&quot;335559740&quot;:240}">&nbsp;</span></li> </ul> <p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 2">Bonus Points!</span></span></strong><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559738&quot;:220,&quot;335559739&quot;:100,&quot;335559740&quot;:240}">&nbsp;</span></p> <ul> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">End-to-end / VLA driving</span></strong><span data-contrast="none"> — familiarity with VLM/VLA or end-to-end driving models, trajectory and action grounding, or chain-of-causation / reasoning-trace datasets.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">Auto-labeling foundation models</span></strong><span data-contrast="none"> — experience with segmentation, open-vocabulary detectors, or VLM/LLM-driven data engines for annotation and verification.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">High-throughput model serving</span></strong><span data-contrast="none"> — vLLM, SGLang, or similar for batch auto-labeling and inference at scale.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">Semantic inference &amp; retrieval</span></strong><span data-contrast="none"> — attribute mapping, semantic search, and vector databases (e.g., LanceDB) for automotive data.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">AV data standards &amp; tooling</span></strong><span data-contrast="none"> — scenario-description standards such as Pegasus layers; parsing robotics formats (ROS bags, MCAP) and optimizing columnar storage (Parquet, Arrow).</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">Cloud development &amp; orchestration</span></strong><span data-contrast="none"> — Terraform and AWS managed services (S3, ECS, Lambda, DynamoDB, Step Functions, Athena); AWS HyperPod / Anyscale; inference orchestration.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">Data visualization</span></strong><span data-contrast="none"> — Foxglove, FiftyOne (51), three.js, OpenGL, or similar for dataset inspection and accessibility.</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="20" data-aria-level="1"><strong><span data-contrast="none">Evaluation &amp; research</span></strong><span data-contrast="none"> — closed-loop / open-loop evaluation frameworks (e.g., NavSim-style planning metrics); publications in top-tier CV/AI/Robotics venues (CVPR/ECCV/ICCV, NeurIPS/ICLR/ICML, CoRL).</span><span data-ccp-props="{&quot;134233279&quot;:false,&quot;201341983&quot;:0,&quot;335559739&quot;:60,&quot;335559740&quot;:240}">&nbsp;</span></li> </ul> <p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 2">Perks of Being a Full-time </span><span data-ccp-parastyle="heading 2">Torc’r</span></span></strong><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559738&quot;:220,&quot;335559739&quot;:100,&quot;335559740&quot;:240}">&nbsp;</span></p> <p><span data-contrast="none">Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p> <ul> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="28" data-aria-level="1"><span data-contrast="none">A competitive compensation package that includes a bonus component and stock options</span> </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="28" data-aria-level="1">100% paid medical, dental, and vision premiums for full-time employees </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="28" data-aria-level="1">401K plan with a 6% employer match </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="28" data-aria-level="1">Flexibility in schedule and generous paid vacation (available immediately after start date) </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="28" data-aria-level="1">Company-wide holiday office closures </li> <li data-leveltext="•" data-font="" data-listid="4" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:540,&quot;335559991&quot;:270,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="28" data-aria-level="1">AD+D and Life Insurance<span data-ccp-props="{&quot;134233279&quot;:false,&quot;201341983&quot;:0,&quot;335559739&quot;:60,&quot;335559740&quot;:240}">&nbsp;</span></li> </ul> <p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 2">Additional Information</span></span></strong><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559738&quot;:220,&quot;335559739&quot;:100,&quot;335559740&quot;:240}">&nbsp;</span></p> <p><span data-contrast="none">At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p> <p><span data-contrast="none">Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc’s total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p> <p><strong><span data-contrast="none">Job ID:</span></strong><span data-contrast="none"> R-102744</span><span data-ccp-props="{&quot;335559739&quot;:120}">&nbsp;</span></p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><span style="text-decoration: underline;"><strong>Hiring Range for Job Opening&nbsp;</strong></span></div><div class="title">US Pay Range</div><div class="pay-range"><span>$177,300</span><span class="divider">&mdash;</span><span>$212,800 USD</span></div></div></div>