Machine Learning Engineer - Biological Analysis & Simulation

ABOUT MITHRLAt Mithrl, we envision a future where innovative medicines are delivered to patients in mere months rather than years, and scientific advancements occur at unparalleled speed.Mithrl is pioneering the development of the world’s first commercially available AI Co-Scientist, a revolutionary discovery engine that swiftly converts complex biological data into actionable insights. Scientists can pose questions in natural language, and Mithrl will provide comprehensive analyses, propose novel targets, formulate hypotheses, and generate patent-ready reports—all in minutes.Our success is evident:Achieved 12X year-over-year revenue growthRecognized by leading biotech firms and major pharmaceutical companies across three continentsFacilitating real breakthroughs from target identification to improved patient outcomes.ABOUT THE ROLEWe are seeking a talented ML Engineer for our Discovery Applications team to create high-level, end-to-end scientific workflows that enhance decision-making within the Mithrl platform. This position focuses on developing the application layer that interacts with our AI Co-Scientist. You will play a crucial role in how scientists uncover biomarkers, validate targets, design experiments, and initiate early discovery programs that lead to IND-enabling studies.A strong understanding of the discovery and preclinical development cycle is essential for this role. You will need to comprehend how research teams transition from early target hypotheses to creating biomarker strategies, hit identification, lead optimization, and preclinical validation. Your applications will directly support decision-making across this continuum and will be utilized by scientists and program teams.Your responsibilities will include designing multi-step workflows that integrate analysis modules, ML models, domain-specific logic, and agentic reasoning into cohesive applications. These applications will encompass biomarker discovery, target identification, target validation, small molecule hit identification and optimization, as well as gene therapy workflows. Furthermore, you will adapt applications to incorporate new data modalities as our platform evolves.

Why Join Achira?Become part of an elite team comprising scientists, machine learning researchers, and engineers dedicated to transforming the predictability of the physical microcosm and revolutionizing drug discovery.Explore uncharted territories: we are on a mission to innovate next-generation model architectures that merge AI with chemistry.Engage in large-scale operations: harness massive computational resources, extensive datasets, and ambitious objectives.Take ownership of significant projects from inception to deployment on large-scale infrastructures.Thrive in a culture that values precision, speed, execution, and a proactive mindset.About the PositionAt Achira, we are committed to developing state-of-the-art foundation models that tackle the most complex challenges in simulation for drug discovery and beyond. Our atomistic foundation simulation models (FSMs) serve as world models of the physical microcosm, incorporating machine learning interaction potentials (MLIPs), neural network potentials (NNPs), and various generative models.We are seeking a Machine Learning Research Engineer (MLRE) who excels at the intersection of advanced machine learning and rigorous research methodologies. Collaborate closely with our research scientists to design and enhance intelligent training systems that propel us beyond contemporary architectures into a new era of ML-driven molecular modeling.Your mission is clear yet ambitious: to establish the foundational frameworks for training atomistic simulation models at scale. This entails a deep dive into architecture, data, optimizers, losses, training metrics, and representation learning, all while constructing high-performance systems that maximize the potential of our models. In this role, you will be instrumental in creating a blueprint for pretraining FSMs similar to today’s large-scale generative AI systems, making a significant impact on drug discovery.At Achira, you will have the chance to pioneer models that comprehend and simulate the physical world at an atomic level, achieving unprecedented speed and accuracy.

About Our TeamAt OpenAI, we are pioneers in the field of artificial intelligence, committed to driving innovation and shaping a future where AI benefits everyone. We seek passionate and visionary Research Engineers to become part of our Applied Voice Team. In this role, you'll engage in transformative research on speech models, translating these insights into real-world applications that can revolutionize industries, enhance human creativity, and tackle complex challenges.About the RoleAs a Research Engineer on OpenAI's Applied Voice Team, you will collaborate with some of the most talented professionals in AI. You will be responsible for designing and developing cutting-edge speech models, including speech-to-speech, transcription, and text-to-speech functionalities. Your work will help translate groundbreaking research into practical solutions for B2B applications, APIs, and ChatGPT AVM. If you are eager to make AI more accessible and impactful, this is your opportunity to leave a lasting legacy.Key Responsibilities:Innovate and Build: Conceptualize and create advanced machine learning models that address real-world challenges, transforming OpenAI's research into AI applications with significant impact.Collaborate with Experts: Partner with software engineers, product managers, and deployed engineers to understand intricate business challenges, respond to customer needs, and deliver AI-driven solutions. Join a vibrant team environment where creativity and ideas flourish.Optimize and Scale: Develop scalable data pipelines, enhance models for improved performance and accuracy, and ensure readiness for production. Contribute to high-tech projects that demand innovative methodologies.Learn and Lead: Stay at the forefront of developments in machine learning and AI by participating in code reviews, sharing insights, and exemplifying high-quality engineering practices.Make an Impact: Oversee and maintain deployed models to ensure they consistently provide value. Your contributions will significantly influence the role of AI in benefiting individuals, businesses, and society as a whole.Ideal Candidate Profile:Master's or PhD in Computer Science, Machine Learning, or a related discipline.A minimum of 2 years of professional experience in engineering roles within technology and product-focused organizations (internships excluded).

Join Lightning AI as a Senior Application Security Engineer specializing in the realms of Artificial Intelligence and Machine Learning. In this pivotal role, you'll be responsible for enhancing our application security posture across our innovative platforms. Collaborate with a team of talented engineers to identify vulnerabilities, implement security best practices, and ensure our AI-driven solutions remain robust and secure.

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.

Join Handshake as a Machine Learning Engineer I, where you will have the opportunity to work on cutting-edge machine learning projects that drive our innovative solutions. Collaborate with a talented team to develop algorithms and models that enhance our product offerings and improve user experiences.

Join Our Innovative Team at HiveHive is at the forefront of cloud-based AI solutions, revolutionizing how organizations understand, search for, and generate content. Trusted by many of the world's largest and most groundbreaking companies, we empower developers with premier pre-trained AI models that handle billions of API requests monthly. Our turnkey software applications leverage proprietary AI models and datasets, driving transformative advancements in content moderation, brand protection, sponsorship measurement, and context-based ad targeting.With over $120M in funding from prominent investors like General Catalyst, 8VC, Glynn Capital, Bain & Company, and Visa Ventures, Hive is rapidly expanding. Our dynamic team of over 250 employees operates from our San Francisco, Seattle, and Delhi offices. If you are passionate about shaping the future of AI, we invite you to explore opportunities with us!About the Machine Learning Engineer RoleAs we strive to achieve our ambitious vision, we seek exceptional machine learning engineers to join our team. We are looking for enthusiastic developers who are eager to remain at the cutting edge of deep learning technology, designing and deploying state-of-the-art neural network models into production. Our ideal candidates thrive in working with large-scale datasets and demonstrate a keen interest in mastering new technologies across the machine learning spectrum. We value individuals who are proactive and take ownership of their projects, contributing innovative ideas and practical implementations. Experience in building machine learning applications from the ground up and designing scalable, maintainable data pipelines is essential.

Join our dynamic Personalization team at Boomtrain as a Machine Learning Engineer. We are in search of a skilled engineer who will play a pivotal role in developing and enhancing our recommendation systems that cater to a variety of customers.In this role, you will collaborate with a talented team dedicated to designing and implementing innovative models and systems that deliver personalized recommendations. You will have the opportunity to work on complex engineering challenges and contribute to generating hundreds of millions of recommendations daily.This position offers a unique chance to engage in end-to-end project work and make a significant impact on our personalization initiatives.Key Responsibilities:Research and propose advanced recommendation and optimization models to enhance our personalization systems.Develop and maintain offline model generation pipelines.Design and maintain online recommendation serving systems.

OverviewPulse is revolutionizing data infrastructure by addressing the critical challenge of extracting accurate, structured information from complex documents on a large scale. Our innovative approach to document understanding integrates intelligent schema mapping with advanced extraction models, outperforming traditional OCR and parsing methods.As a dynamic and rapidly growing team of engineers based in San Francisco, we empower Fortune 100 companies, Y Combinator startups, public investment firms, and growth-oriented businesses. With the backing of top-tier investors, we are on an exciting growth trajectory.What sets our technology apart is our cutting-edge multi-stage architecture:Layout comprehension with specialized component detection modelsLow-latency OCR models designed for targeted data extractionAdvanced algorithms for determining reading order in complex formatsProprietary table structure recognition and parsing capabilitiesFine-tuned vision-language models for interpreting charts, tables, and figuresIf you are passionate about the convergence of computer vision, natural language processing, and data infrastructure, your contributions at Pulse will directly influence our customers and shape the future of document intelligence.

Join Handshake as an Associate Machine Learning Engineer and embark on an exciting journey in the world of artificial intelligence and machine learning. In this role, you will collaborate with a talented team to develop innovative solutions that leverage cutting-edge technologies. You'll have the opportunity to contribute to real-world projects, enhancing your skills while driving impactful results.

Cheminformatics and Machine Learning InternGenesis Molecular AI is assembling a premier computational team dedicated to creating the industry’s most rapid and precise small molecule property predictions by harnessing the synergy of machine learning and physics-based methods. We invite early-career scientists who excel in the development and application of machine learning, physics, and cheminformatics techniques to advance our ambitious drug discovery initiatives.About the RoleIn this role, you will be an integral part of our machine learning and cheminformatics team, contributing significantly to our internal ML and physics-based platform that propels our drug discovery projects forward.Your responsibilities will likely encompass developing innovative methodologies for potency and ADME/PK property prediction, as well as prototyping integrations with cutting-edge molecular modeling tools.Your ResponsibilitiesLead a groundbreaking research project from concept to implementation, aimed at enhancing our internal tools for potency and ADME prediction.Prototype innovative approaches based on recent academic publications. Design and conduct large-scale experiments to validate promising findings using both internal and public benchmarks.Collaborate closely with our computer-aided drug discovery scientists and medicinal chemists to develop, benchmark, and implement enhancements to our drug discovery platform as it relates to our internal and partnered drug discovery efforts.Your ProfileA graduate student with a strong track record in developing cheminformatics tools and/or physics methods relevant to drug discovery.Proficient in Python programming with a demonstrated ability to navigate and contribute to complex codebases.An experienced machine learning practitioner with familiarity in common architectures and proven skills in troubleshooting real-world applications.A detail-oriented data scientist adept at managing diverse data sources. Familiarity with RDKit, OpenEye, and other cheminformatics libraries is a plus.Passionate about making a tangible impact on drug discovery projects and engaging with a diverse team of ML practitioners, medicinal chemists, and drug discovery scientists.

Charter:Join us as a pivotal member of a groundbreaking team dedicated to revolutionizing the field of toxicology by developing advanced AI systems that will replace traditional lab and animal experiments.What We Seek:We are on the lookout for exceptional individuals who can inspire those around them and drive the team towards greatness. Our ideal candidate is someone with high agency—able to identify priorities and take action. We value unique passions and hobbies that may seem niche but reveal a deep commitment and curiosity when explored. Candidates should approach challenges with both intentionality and a sense of wonder, embodying the spirit of exploration akin to an immigrant in a new land or a self-taught coder. A strong desire to learn and grow, coupled with technical excellence and a commitment to mastering one’s craft, is essential. We want those who are willing to tackle daunting challenges and derive satisfaction from the journey as much as the outcome.Your Responsibilities:Establish the foundational end-to-end ML/AI system, including wetlab data generation, data cleaning/processing, model architecture, training, inference, and deployment strategies.Lead innovative research and development initiatives focused on elucidating the interplay between chemistry and biology.Design and scale large models that are pretrained on paired chemistry and biological imagery.Conduct applied research aimed at optimizing, aggregating, and pooling embeddings.Become a thought leader in emerging and underexplored domains, such as molecular graph representations and generative diffusion for biological applications.Develop entrepreneurial skills alongside engineering expertise by creating impactful solutions that deliver substantial value for scientists.Deliver outstanding technology and products that redefine industry standards.Preferred Attributes:...

Position: Machine Learning EngineerAbout Us:At UnitX, we are pioneering the development of cutting-edge physical AI systems designed to automate repetitive visual tasks within manufacturing environments. Our dynamic startup thrives on a diverse team of experts from renowned institutions such as Stanford, MIT, and Google. To date, we have successfully implemented over 1,000 mission-critical AI systems across more than 190 of the world's top manufacturing production lines. Annually, our AI inspection systems oversee the quality of products valued at $15 billion.Join us for a unique opportunity to contribute to groundbreaking computer vision technologies that are transforming global manufacturing efficiency.Your Responsibilities:Design and implement innovative algorithms to analyze raw sensor data for defect detection, focusing on pixel-level precision in high-resolution image and 3D data segmentation.Develop robust software solutions that operate continuously on production lines, executing our algorithms in real-time with decision-making latency under 20ms.Create metrics and tools for comprehensive model performance evaluation, enhancing system visibility and interpretability.Research and explore novel methodologies, pushing the boundaries of AI technology, including Stable Diffusion and SAM, to deliver critical applications in manufacturing.Who You Are:Bachelor's degree in Computer Science, Mathematics, Physics, or a related technical discipline, or equivalent experience showcasing solid mathematical foundations.A minimum of 2 years of experience developing machine learning models focused on computer vision applications in production settings.Deep understanding of Deep Learning theories and practical applications, with proficiency in frameworks such as PyTorch or TensorFlow. Strong Python programming skills for creating efficient, maintainable solutions within extensive codebases.Excellent communication and decision-making abilities, able to articulate experimental rationale and judiciously navigate between exploration and exploitation strategies.Demonstrated resilience and adaptability in complex, uncertain environments.Preferred Qualifications:Experience with large-scale data processing and algorithm optimization.Familiarity with tools for machine learning and data visualization.

Join Hive as a Senior Machine Learning Engineer and help shape the future of AI! We are seeking passionate individuals who excel at developing and deploying cutting-edge deep learning models. In this role, you will work with large-scale datasets to create innovative machine learning solutions, collaborating closely with a talented team of engineers to push the boundaries of artificial intelligence. Ideal candidates will have a proven track record of building and scaling machine learning projects from conception to production, along with a strong commitment to continuous learning and personal ownership in their work.

Be Part of the Future of Autonomous RoboticsAt Bedrock Robotics, we are pioneering the transition of AI from theoretical frameworks to practical applications in the built environment. Our team is comprised of seasoned professionals who have been instrumental in the success of innovative companies such as Waymo, Segment, and Uber Freight. We are at the forefront of deploying autonomous technologies in heavy construction machinery, significantly enhancing the efficiency and safety of multi-billion dollar infrastructure projects across the nation.With backing from $350 million in funding, our mission is to address the urgent need for housing, data centers, and manufacturing facilities, while simultaneously responding to the construction industry's labor shortages.This position is where cutting-edge algorithms meet the practical world of construction. You will work alongside industry experts and top-tier engineers to tackle complex real-world challenges that cannot be simulated. If you are eager to leverage advanced technology for impactful problem-solving within a skilled team, we encourage you to apply.

Company Overview At Specter, we are pioneering a software-defined "control plane" designed to enhance the real-world perception of physical assets. Our mission begins with safeguarding American businesses by providing them with comprehensive insights into their physical environments.To achieve this, we are developing a robust hardware-software ecosystem leveraging multi-modal wireless mesh sensing technology. This innovation allows us to significantly reduce the cost and time involved in sensor deployment by a factor of ten. Ultimately, our platform aims to serve as the perception engine for businesses, facilitating real-time visibility and autonomous management of their operational perimeters.Our co-founders, Xerxes and Philip, are deeply committed to empowering our partners in the rapidly evolving landscape of physical AI and robotics. We are a dynamic, rapidly expanding team comprised of talent from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview Specter is seeking a dedicated Machine Learning Infrastructure Engineer to construct and optimize the ML systems that drive real-time perception and inference capabilities across our edge-cloud platform. This position will involve overseeing the training, deployment, and enhancement of computer vision and sensor fusion models, aimed at enabling autonomous monitoring and decision-making for our clients' physical assets.Key Responsibilities Include:Design and implement scalable ML training pipelines for computer vision applications, including object detection, tracking, classification, and segmentation.Develop efficient model serving infrastructures to facilitate real-time inference on edge devices with limited computational and power resources.Optimize models for deployment on embedded hardware, employing techniques such as quantization, pruning, TensorRT, ONNX, and CoreML.Create continuous training and evaluation systems to enhance model performance through feedback loops derived from production data.Establish data pipelines for the ingestion, labeling, versioning, and management of extensive multi-modal sensor datasets, including video, radar, lidar, and thermal data.Implement model monitoring frameworks, A/B testing methodologies, and performance analytics for deployed perception systems.Collaborate with perception researchers to transition models from research environments to scalable production across thousands of edge nodes.Construct tools and infrastructure for distributed training, hyperparameter optimization, and experiment tracking.

Join Reducto as a Machine Learning Evaluation Engineer where you will play a critical role in assessing and enhancing machine learning models. You will collaborate closely with data scientists and engineers to ensure our systems are efficient and accurate, bringing innovative solutions to challenging problems in the machine learning space.

Saris AI, based in San Francisco with teams in Montreal and Toronto, develops advanced agentic AI systems for the banking industry. The company focuses on automating complex workflows that require long-context reasoning, integration with legacy systems, and strict compliance. With live AI agents already supporting real customer operations, Saris AI is expanding quickly and seeking technical leaders who want to shape the future of work in banking. Role overview This is a hands-on leadership position within the core engineering team in San Francisco. The Machine Learning Engineering Lead will guide machine learning systems from initial concept through scaling, helping define both the technical vision and the supporting infrastructure. What you will do Oversee the ML/AI function end to end, setting technical direction and standards across the company. Design and supervise development of multi-modal, agentic AI systems that power live customer workflows. Build and manage evaluation frameworks, datasets, and metrics to improve agent performance. Drive productionization of ML systems with an emphasis on reliability, scalability, and compliance. Recruit, develop, and mentor a high-performing ML team, fostering strong practices in modeling, experimentation, and deployment. Requirements 8+ years of experience in machine learning or AI engineering, including time as a technical lead or manager. Proven track record leading ML projects from concept to production deployment. Expertise with large language models (LLMs) and/or agentic systems, especially in customer-facing products. Strong grasp of ML fundamentals: deep learning, transformers, model evaluation, and trade-offs. Hands-on experience scaling ML systems in production, with a focus on monitoring, iteration, and reliability. Ability to lead engineering teams, influence architecture, and set technical direction. Comfort working in early-stage, ambiguous, and rapidly changing environments.

About Scribd:At Scribd Inc. (pronounced 'scribbed'), we're on a mission to ignite human curiosity. Join our innovative team as we craft a diverse world of stories and knowledge, democratizing the exchange of ideas and empowering collective intelligence through our four flagship products: Everand, Scribd, Slideshare, and Fable.This job posting is for an exciting, open position within our organization.We foster a culture where authenticity and boldness thrive, facilitating open debates and commitments as we embrace the unexpected. Every team member is empowered to take initiative, prioritizing the needs of our customers.In terms of workplace structure, we prioritize a balance between personal flexibility and communal connections. Our Scribd Flex initiative allows employees, in collaboration with their managers, to determine their daily work styles that best suit their individual needs while promoting intentional in-person interactions to enhance collaboration and company culture. Therefore, occasional in-person attendance is mandatory for all employees, regardless of their location.What do we seek in our new team members? We value 'GRIT'—the intersection of passion and perseverance toward long-term goals. At Scribd Inc., we believe in harnessing the potential that GRIT unlocks and encourage each employee to adopt a GRIT-driven approach to their work. This means we are looking for individuals who can set and achieve Goals, deliver Results in their responsibilities, contribute Innovative ideas, and positively impact the broader Team through collaboration and a positive attitude.About Our Machine Learning Team:Our Machine Learning team is pivotal in developing the platform and product applications that drive personalized discovery, recommendations, and generative AI functionalities across Scribd, Slideshare, and Everand. The ML team operates on the Orion ML Platform, providing essential ML infrastructure such as a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). Our Machine Learning Engineers collaborate closely with the Product team to integrate machine learning into user-facing features, including real-time personalization and AskAI LLM-powered experiences.