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Dice
Menlo Park, CA, United States
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Meta Platforms, Inc. (f/k/a Facebook, Inc.), is seeking the following. Apply via Dice today! Meta Platforms, Inc. (f/k/a Facebook, Inc.) has the following position in Menlo Park, CA: Machine Learning Engineer: Research, design, develop, and test o
Job Source: DiceHP Development Company, L.P.
Palo Alto, CA, United States
Machine Learning Engineer Description - Job Description You are out to reimagine and reinvent what is possible-in your career as well as the world around you. So are we. We love taking on tough challenges, disrupting the status quo, and creating what is next. We are in search of talented people who are inspired by big challenges, driven to learn
Job Source: HP Development Company, L.P.Ntropy
San Francisco, CA, United States
While significantly more efficient than humans for many tasks, the cost and latency of LLMs is still prohibitive for most real world applications. At Ntropy, our mission is to make LLMs viable at scale. We are developing a new kind of domain-specific wrappers for language models, that leads to a reduction in the number of queries to the base model
Job Source: NtropyHelm.ai
Redwood City, CA, United States
We help make autonomous technologies more efficient, safer, and accessible. Helm.ai builds AI software for autonomous driving and robotics. Our "Deep Teaching" methodology is uniquely data and capital efficient, allowing us to surpass traditional approaches. Our unsupervised learning software can train neural networks without the need for human an
Job Source: Helm.aiRobust Intelligence
San Francisco, CA, United States
Robust Intelligence's mission is to eliminate AI Risk. As the world increasingly adopts AI into automated decision processes, we inherit great risk. Our flagship product is built to be integrated with existing AI systems to enumerate and eliminate risks caused by unintentional and intentional (adversarial) failure modes. With Generative AI becomin
Job Source: Robust IntelligenceKind Humanoid
Palo Alto, CA, United States
Why Kind Humanoid I have started building an intelligent humanoid because I could not think of a more intriguing challenge than reproducing human level motion capabilities and human level task solving intelligence. We are building the company Kind Humanoid because we want to deploy humanoids to provide additional labor to build an inspiring tomorro
Job Source: Kind HumanoidProbably Genetic
San Francisco, CA, United States
About Probably Genetic: Probably Genetic is changing the lives of patients living with severe, complex diseases. Our data platform is used by drug developers and patient advocacy groups to develop and launch treatments for these patients. Our technology discovers undiagnosed patients online, analyzes their disease state using machine learning and a
Job Source: Probably GeneticTigerGraph
Redwood City, CA, United States
TigerGraph Is a Platform For Advanced Analytics And Machine Learning On Connected Data. TigerGraph's Core Technology Is The Only Scalable Graph Database For The Enterprise. Its Proven Technology Supports Fraud Detection, Customer 360, MDM, IoT, AI, And Machine Learning. Fortune 500 Organizations And The Most Innovative Mid-size And Startup Companie
Job Source: TigerGraphSan Mateo, CA, United States
The Role: We are seeking a self-motivated, experienced Machine Learning Engineer* to develop, deploy, and refine tools to accelerate our antibody design cycle. *At BigHat we believe in titles that are commensurate with skill set, relative organizational impact, and value contribution; more experienced candidates are encouraged to apply, with the understanding that responsibilities and title would adjust as appropriate. At BigHat Biosciences, our machine learning stack is tightly integrated with a high-throughput wet lab to rapidly design, validate, and iteratively refine the first generation of ML-engineered antibody therapeutics. Our bespoke platform channels data from automated lab instruments to data processing pipelines, custom validation and QC, ML data ingestion ETLs, and finally, through predictive ML models and sequence optimization algorithms which produce the next set of antibody designs, ideally one step closer to a beneficial therapeutic but always generating valuable training data. You’re not interested in any model thrown at any data. Motivated by an enthusiasm for the possibility of addressing unmet patient need, and a curiosity about the underlying biology, as an ML Engineer you’ll apply your world-class ML skillset to refine and expand this state-of-the-art protein engineering platform, improving the effectiveness with which it can be used to design new therapeutics. Job Responsibilities
Rapidly implement, evaluate and deploy predictive machine learning models of diverse antibody biophysical properties, for dataset scales from hundreds to millions, to support BigHat’s therapeutic portfolio.
Design and develop production-grade infrastructure for better model training, tracking, benchmarking and lab validation, across diverse tasks in a continuous data generation setting.
Accelerate our multiobjective antibody optimization programs by developing, identifying or refining data- and domain-appropriate ML-driven protein sequence design tools.
Work closely with ML and DS team members to identify inefficiencies or potential improvements and coordinate or implement solutions.
Provide support for ongoing ML-guided antibody engineering therapeutics programs at BigHat.
Collaborate closely with BigHat engineering, data science, and lab teams to ensure ML tooling is tailored to our experimental platform and therapeutic development goals.
Preferred Qualifications
BS/MS 5/3+ years of hands-on experience crafting, refining and deploying ML models in the wild.
Strong competency in Python, familiarity with pytorch, experience deploying ML and DS stacks on AWS.
Experience with relational databases, RESTful APIs.
Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
Enjoys a fast paced environment and executing across multiple projects.
Nice-to-haves include experience with protein structure modeling and biophysics, NGS data, and front-end (React).
About BigHat Biosciences
BigHat Biosciences designs safer, more effective biologic therapies for patients using machine learning and synthetic biology.
BigHat integrates a wet lab for high-speed characterization with machine learning technologies to guide the search for better antibodies. We apply these design capabilities to develop new generations of safer and more effective treatments for patients suffering from today’s most challenging diseases.
BigHat is a Series B biotech outside San Francisco with a team-oriented, inclusive, and family-friendly culture. Our broad pipeline of wholly-owned and partnered therapeutic programs span many disparate indications with high unmet need, such as cancer, inflammation, and infectious disease. BigHat has raised >$100M from top investors, including Section 32, a16z, and 8VC.
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Email Alert for Machine Learning Engineer jobs in San Mateo, CA, United States
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