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Machine learning engineer Jobs in Carlsbad, CA
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Machine learning engineer • carlsbad ca
- Promoted
Machine Learning Scientist
Inductive BioCarlsbad, California, United StatesStaff Software Engineer - Machine Learning (MLOps)
CrunchbaseCalifornia, United States- Promoted
Operator I-Machine
WestlakeOceanside, CA, USLIFELONG LEARNING
Santa Rosa Junior CollegeSonoma County, CAMachine Operator
AtWorkCarlsbad- Promoted
Machine Operator (1st Shift)
Vive OrganicOceanside, CA, USMachine Operator - TalentZok
TalentZokVista, CA, USMachine Operator (1st Shift)
Coneybeare LLCOceanside, California, United StatesSenior Machine Learning Engineer, Financial Crimes (Cash App)
SquareRemote, CA, USMachine Operator
Malone Workforce SolutionsVista, CA- Promoted
Retail Learning & Development Content Designer
Vuori, IncCarlsbad, CA, USMachine Operator
AerotekOceanside,CA,92049,USADigital Learning Executive
WileyCalifornia, USA- Promoted
Retail Learning & Development Content Designer
VuoriCarlsbad, CA, USStaff Machine Learning Engineer
AngiCalifornia2nd shift Machine Operator
VoltCarlsbad, CA, United States- Promoted
Machine Learning Engineer
VirtualVocationsVista, California, United StatesSenior Performance Engineer - Deep Learning
NVIDIARemote, CA, US- Promoted
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Floor Tech - Machine Operator
ABM IndustriesCarlsbad, CA, USExpanded Learning After School Programs
RIVERSIDE UNIFIED SCHOOL DISTRICTRiverside County, CA, USThe average salary range is between $ 130,000 and $ 192,280 year , with the average salary hovering around $ 130,000 year .
- psychiatrist (from $ 17,561 to $ 287,625 year)
- telecommute (from $ 122,400 to $ 246,000 year)
- government (from $ 76,045 to $ 221,936 year)
- waste management (from $ 39,520 to $ 219,050 year)
- clinic director (from $ 122,960 to $ 205,800 year)
- clinical psychologist (from $ 151,125 to $ 197,600 year)
- live in nanny (from $ 18,244 to $ 195,000 year)
- backend developer (from $ 114,375 to $ 195,000 year)
- aerospace (from $ 39,000 to $ 194,700 year)
- architect (from $ 105,625 to $ 193,500 year)
- Lansing, MI (from $ 114,400 to $ 241,000 year)
- Cedar Rapids, IA (from $ 131,250 to $ 240,706 year)
- Grand Rapids, MI (from $ 133,750 to $ 240,706 year)
- Kent, WA (from $ 109,500 to $ 238,773 year)
- Simi Valley, CA (from $ 145,000 to $ 235,450 year)
- Spokane Valley, WA (from $ 145,000 to $ 235,450 year)
- Sunnyvale, CA (from $ 154,550 to $ 230,000 year)
- Bellevue, WA (from $ 140,000 to $ 229,250 year)
- Wichita Falls, TX (from $ 159,200 to $ 226,625 year)
- Austin, TX (from $ 144,900 to $ 225,000 year)
The average salary range is between $ 124,693 and $ 200,000 year , with the average salary hovering around $ 154,997 year .
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Machine Learning Scientist
Inductive BioCarlsbad, California, United States- Full-time
Drug discovery is a prediction problem. Scientists design molecules that they predict will be potent, safe, and readily absorbed into the body, but ultimately lab experiments must be run to know whether these predictions are accurate. Each one of these experiments can take weeks or months to run, and as a result it costs millions of dollars and takes years to design a molecule that is ready for testing in humans.
At Inductive Bio, we're using AI to build in silico models that can more accurately predict how molecules will behave in experiments. By predicting complex molecular properties directly from the molecular structure, our platform helps scientists make better decisions faster—ultimately bringing safer, higher-quality medicines to patients more quickly. We are enabled by a unique and growing proprietary data set, and we are already applying our methods to dozens of active drug discovery programs. Backed by leading investors at the intersection of biotechnology and technology and advised by renowned experts in drug discovery, we are growing rapidly and poised to make a major impact in drug discovery.
We are seeking Machine Learning Scientists to join our talented, ambitious, and kind team. You'll have the opportunity to innovate on methods, work with leading drug discovery scientists, and apply your work immediately to drug programs at some of the most innovative biotechs in the world. As an early machine learning scientist at a rapidly-growing startup, you’ll have the opportunity for high impact while learning and growing with the company.
What you’ll do :
Develop machine learning models to predict molecular properties from chemical structures
Develop novel algorithms for generating ideas for new molecules
Build agents that can synthesize complex information from drug programs and apply that information strategically toward molecular optimization
Get your hands dirty by diving deep into our unique, proprietary dataset to iterate on modeling ideas and improve model performance
Collaborate closely with chemists and software engineers to integrate models into our software platform, which is used by drug discovery scientists across the industry
Build and optimize scalable infrastructure for model training, deployment, and monitoring
Engage directly with our scientific users, incorporating their feedback into the product
Contribute meaningfully to product strategy and company direction
Who you are :
You have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, Data Scientist, or similar role
You have expertise in machine learning fundamentals, deep learning architectures, and evaluation approaches
You are proficient in standard Python-based ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)
You are comfortable writing high-quality, reusable code and productionizing models for serving in the cloud
You are excited to dive deep into the science and practice of drug discovery
You have exceptional written and oral communication skills
Working at Inductive
At Inductive Bio, we know that the people on the team are what make us great. We offer competitive salary and equity-based compensation; comprehensive healthcare benefits (including dental and vision); and the opportunity to grow along with a rapidly scaling company. We are a passionate, kind, and mature team. Working at a fast growing startup is not always a 9-5 job, but we believe that our employees should have full lives beyond their career.