Machine Learning Engineer Jobs

Lila is revolutionizing biomedicine by integrating large-scale automated data generation with advanced AI. We are building a system where AI, automation, and experimental biology work together synergistically. This role focuses on connecting that work to human medicine by developing systems that evaluate the biological validity of clinical programs. You will build the infrastructure to assess mechanistic support, ground biological mechanisms in human data, and evaluate clinical trial designs against proposed mechanisms. The goal is to create scalable systems that can rigorously assess and forecast program outcomes, ensuring scientific integrity and enabling public dissemination of findings.

$268k - $384k

We are seeking an engineer with expertise in low-level systems programming and optimization to join our expanding ML team. Machine learning is a crucial component of Jane Street's global business, and our dynamic trading environment provides a unique platform for rapid ML experimentation. Your primary role will be to optimize the performance of our machine learning models, encompassing both training and inference. This involves ensuring efficient large-scale training, low-latency inference for real-time systems, and high-throughput inference for research. The work requires a holistic systems approach, considering storage, networking, and host/GPU-level factors, down to the most granular details of hardware performance.

Salary not listed

Cargo

Plaid is seeking a Staff Machine Learning Engineer to join the Data Foundation & AI team. This team builds the shared ML and AI infrastructure that powers intelligent capabilities across Plaid's product suite, transforming unique financial network data into scalable, general-purpose representations. The role involves working at the intersection of machine learning infrastructure, applied AI, and distributed systems to establish the core AI platform that enables innovation. The Staff ML Engineer will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches. This position requires establishing rigorous evaluation frameworks, building scalable pipelines, and partnering with teams across the organization to define product integrations with foundation models. As a senior technical leader, you will mentor engineers, elevate engineering standards, and represent Plaid's AI and machine learning capabilities externally.

$249k - $368k

Ema builds AI Employees for HR, IT, and Finance, automating busy work across the employee experience. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team comprises engineers from premier tech companies and graduates of top universities. We are backed by leading investors and are at the forefront of Agentic AI, shipping real systems that run business processes at scale. We are seeking innovative and passionate Machine Learning Engineers who excel at solving complex problems with large datasets, transforming theoretical concepts into practical, scalable solutions, and pushing the boundaries of Natural Language Processing and Information Retrieval.

$160k - $220k

We are seeking a mathematically rigorous engineer to own model numerics, focusing on how we measure, bound, and reason about the numerical behavior of models and how this analysis informs deployment decisions. The core challenge involves determining if numerical differences between model versions are safe, connecting low-level concepts like floating-point drift to high-level outcomes like vehicle trajectory error. You will build the tooling to quantify these connections and define the thresholds for ship/no-ship decisions. This role requires more than just running existing validation; it demands the ability to investigate and explain the root causes of numerical divergence.

$171k - $261k

Databricks

Databricks is seeking a Staff Software Engineer for its AI Runtime (AIR) team. AIR is a managed platform designed for large-scale GPU training and fine-tuning of state-of-the-art AI models, providing customers with on-demand access to accelerators and a serverless experience. As part of this role, you will be instrumental in building and scaling the systems that ensure fast, reliable, and effortless large-scale training. You will influence the architecture and development of the managed GPU training stack, focusing on areas like scheduling, distributed training performance, fault tolerance, and the overall developer experience for operating jobs at scale. This position also involves defining the long-term technical vision for AIR, mentoring senior engineers, and collaborating with product, research, and platform teams to expand the impact of custom training at Databricks.

$190k - $265k

Lila is revolutionizing medicine by integrating automated large-scale data generation with scientific superintelligence. We are building a system where AI, automation, and experimental biology work together to tackle complex medical challenges. The Life Science AI team focuses on developing machine learning systems for analyzing biological data, combining advanced ML with cutting-edge biology. This role is crucial for building domain models that understand perturbation biology, genetics, and high-dimensional experimental data, linking biological mechanisms, experimental interventions, and therapeutic opportunities. The work involves not just learning from data but also guiding data generation and ensuring model outputs are interpretable and actionable for scientists and downstream systems.

$268k - $358k

The Robotic Visual Perception and Learning research group at NVIDIA is seeking highly motivated PhD students for research internships. This role focuses on pushing the boundaries of computer vision, robotics, and machine learning with real-world impact. Interns will have the opportunity to publish their work in top-tier conferences and collaborate with experienced mentors, with carefully crafted projects tailored to their expertise.

$0k - $0k

Lila Sciences is developing a platform where AI and automation collaborate to address complex challenges in medicine, specifically within Life Sciences AI. The AI for Protein Engineering team focuses on creating and implementing generative and predictive models to advance biomolecule design programs from initial concepts to validated leads. This role is for a senior individual contributor specializing in computational biologics design, working on active protein engineering projects and enhancing Lila's capabilities in designing, evaluating, and learning from biomolecular data. The position is at the nexus of machine learning, protein engineering, and therapeutic design, requiring deep ML expertise, a strong understanding of protein biology, and a proven ability to deliver computationally designed, validated biologics.

$268k - $358k

Lila Sciences is seeking a Principal Machine Learning Engineer to join their growing Applied AI organization. This role focuses on adapting and improving AI models for customer-specific scientific needs, bridging the gap between cutting-edge model capabilities and real-world applications. You will be instrumental in shaping how Lila's AI models are fine-tuned, evaluated, and integrated into reliable workflows for customers. This is a senior individual contributor position requiring deep, hands-on expertise in model post-training, evaluation, and production ML systems.

$252k - $336k

Lila Sciences is developing a platform where AI and automation work together to tackle complex problems in medicine. The AI for Protein Engineering team focuses on creating and using generative and predictive models to advance biomolecule design programs from initial concepts to validated leads. This role is at the intersection of machine learning, protein engineering, and therapeutic design, requiring strong ML fundamentals, a curiosity for protein biology, and an interest in computationally designed, wet-lab-validated biologics. You will collaborate with experimental scientists, AI researchers, and platform teams to build models and workflows that support Lila’s autonomous science platform.

$176k - $304k

Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine, specifically in protein engineering. The AI for Protein Engineering team develops models and systems to advance biologics from design to validation. This role involves designing molecules for active biologics programs, developing reasoning capabilities for drug discovery, and creating evaluation infrastructure to ensure design workflows are effective and generalizable across programs. The position requires owning the operational aspects of computational design workflows, including reproducibility, throughput, and inference cost, and translating domain scientist judgment into machine learning objectives.

$176k - $304k

Lila Sciences is building an operating system for science, powered by scientific superintelligence. The Molecular Intelligence team focuses on building ML and physics-based infrastructure for drug discovery, including biophysics workflows, computational chemistry tools, and simulation workflows. This role involves embedding with scientists and collaborating with platform teams on storage, compute, and orchestration. The core of the work is building a provenance system to track scientific inputs, code versions, models, runs, and results across various workflows, enabling scientists to easily find, trace, and reuse discoveries.

$148k - $240k

Lila Sciences is seeking a Staff Engineer to lead the technical direction of its core data infrastructure. This role involves designing and evolving systems for ingesting, storing, and serving data critical to scientific discovery and machine learning workflows. You will work closely with scientists and researchers to translate requirements into robust platform capabilities, establish architectural patterns and engineering standards, and mentor other engineers. The position is ideal for individuals passionate about data system design who want to make impactful technical decisions.

$192k - $288k

Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine. Within Life Science AI, Machine Learning engineers build and operate systems that transform foundation models into production capabilities for automated scientific discovery. This Principal ML Engineer role focuses on designing, building, and scaling the ML infrastructure behind these models, with current work in structure prediction, co-folding, sequence design, and multimodal scientific reasoning. You will own critical systems end-to-end, from training pipelines and distributed compute to model deployment and integration into Lila's discovery engine, shaping the technical direction for ML model training, evaluation, and deployment at scale.

$268k - $384k

Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine. The Foundation Models team within Life Science AI (LSAI) focuses on developing foundation models that integrate biological sequence, molecular structure, and experimental data to drive automated scientific discovery. This role involves contributing to problem formulation, model design, training, evaluation, and integration into Lila's discovery engine, with a specific emphasis on structure prediction and co-folding for antibody and biologics design. The position is for an individual contributor focused on building deep expertise in structure-aware generative AI for biology, owning research sub-problems, and collaborating with experimental scientists to close the computational-experimental loop.

$176k - $304k

We are seeking a Staff or Principal Software Engineer to join our Scientific System of Record Team and help define and build the next-generation AI-driven scientific platform. In this role, you will serve as a technical leader for systems that connect scientific intent, laboratory execution, data capture, and AI-driven analysis. You will shape the architecture of user interfaces, services, high-performance APIs, databases, and reliability-critical systems that integrate advanced AI frameworks with complex scientific analytics and laboratory workflows. You’ll work closely with ML researchers, platform engineers, data engineers, product teams, and scientists to turn complex scientific processes into scalable, elegant software systems. This is an opportunity to set technical direction for a cutting-edge AI platform with real scientific impact.

$204k - $310k

Lila Sciences is seeking a Principal Software Engineer, Instrument Simulations to architect and lead the development of their next-generation laboratory automation platform. This role involves designing the simulation infrastructure and integration layer that connects AI-driven experimental design with physical robotic systems, enabling closed-loop scientific discovery at scale. The company is building Scientific Superintelligence™ to solve humankind's greatest challenges by combining advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously.

$204k - $272k

Lila's Physical Science AI team leverages AI to accelerate discovery in materials and chemistry, contributing to the company's mission of building Scientific Superintelligence. As a Machine Learning Engineer, you will act as a crucial link between research and production, transforming models and agentic workflows developed by scientists and researchers into reliable, scalable systems. The role emphasizes strong software engineering skills and practical experience in deploying ML systems to production, with a scientific background being a beneficial but not essential attribute. Curiosity and a passion for scientific discovery are key to thriving in this position.

$180k - $298k

Lila Sciences is seeking a Software Engineer to join a team that builds software powering the company's ML workflows and research tooling. You will collaborate with Machine Learning Engineers and Researchers to develop, support, and maintain Lila's ML libraries and tools. This role involves designing and building high-performance, secure, and well-documented Machine Learning libraries, creating CI/CD pipelines and integration tests for ML workflows, and architecting repository designs to follow consistent standards. You will also support debugging, logging, and maintenance for Ray-based compute environments and develop data ingestion pipelines linking lab data to ML teams.

$144k - $240k

EnCharge AI is developing a next-generation AI platform featuring a novel in-memory-computing architecture designed to significantly improve energy efficiency and performance for AI inference workloads. We believe that as AI demands evolve, the underlying infrastructure must also advance. Our team, comprised of experienced AI researchers, silicon and systems engineers, and architects, is backed by leading investors and is positioned to be a key player in the future of AI innovation.

Salary not listed

NVIDIA is at the forefront of the AI-City and self-driving revolution, providing powerful GPU-accelerated solutions. This internship offers an opportunity to contribute to the development of AI solutions for self-driving cars, which are increasingly reliant on AI. Interns will work on GPU computing aspects, leveraging NVIDIA's advanced libraries and hardware.

Salary not listed

Magna Electronics is seeking a Machine Learning Engineer to join their Research and Development team. This role involves creating new features for potential products by analyzing state-of-the-art architectures and algorithms, proposing and implementing Proof of Concept projects. You will use your creativity to build these projects from scratch, including data collection, annotation, cleaning, model creation, training, optimization, and demonstrations. The position also requires implementing algorithms for computer vision and signal processing to support research and optimize existing product development.

From $140k

The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models. We operate at the intersection of software engineering, data engineering, and AI/ML, defining strategies, tooling, and quality controls for reliable training data at scale. This role offers end-to-end ownership of meaningful platform components, growth toward technical leadership, and direct impact on systems enabling the next generation of autonomous vehicle capabilities.

$175k - $261k