Machine Operator Integrator Jobs

Company Overview Accordion works at the intersection of sponsors and management teams throughout every stage of the investment lifecycle, providing hands-on, execution-focused support to elevate data and analytics capabilities. So, what does it mean to work at Accordion? It means joining 1,000+ analytics, data science, finance & technology experts in a high-growth, agile, and entrepreneurial environment while transforming how portfolio companies drive value. It also means making your mark on Accordion’s future—by embracing a culture rooted in collaboration and a firm-wide commitment to building something great, together. Headquartered in New York City with 10 offices worldwide, Accordion invites you to join our journey. Data & Analytics (Accordion | Data & Analytics) Accordion's Data & Analytics (D&A) team delivers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges. We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics. D&A team delivers data and analytical solutions designed to streamline reporting capabilities and enhance business insights across vast and complex data sets ranging from Sales, Operations, Marketing, Pricing, Customer Strategies, and more. Role Overview: As Director - Data Science you will be leading one or more client projects to deliver various Advance Analytic solutions. (S)he would be working directly with the clients and guide the team in building a robust solution solving client’s business problem as per agreed timelines through application of business knowledge, project management and technical expertise. What You will do: We expect you to manage a team and work on complex, cross-functional analytical and research-oriented projects u

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: At Cohere, we believe in the power of multimodal AI to revolutionise the way we interact with technology. Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey. With an exceptional ratio of compute resources to engineers, we provide an ideal environment for you to explore, innovate and shape the future of AI. On July 31st 2025, Cohere's Multimodal team Introduced Command A Vision: Multimodal AI Built for Business. At release our new flagship vision-language model: ● Consistently outperforms major models like Llama 4 Maverick, Mistral Medium/Pixtral Large, and GPT4.1 ● 83.1% average benchmark (73.5% MathVista, 90.9% ChartQA...) ● Built for the real world - 112B parameters running on just 2 GPUs ● Open weights live on HuggingFace With a focused team, breakthrough performance doesn't require breakthrough compute. Focus on the things that matter, and join the team. This role is perfect for you if you: Have a deep passion for machine learning and its potential to impact various industries through multimodal applications. Enjoy tuning

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role: A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team. Responsibilities: Perform rigorous and innovative research to discover systematic anomalies in the equities market End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation Identify and evaluate new datasets for stock return prediction Maintain and improve portfolio trading in a production environment Contribute to the analysis framework for scalable research Requirements: MS or PhD in a quantitative discipline 0-2 years of professional work experience A background in financial markets is not necessary, but an interest in the field is essential Proven expertise in Python and handling large datasets Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus Highly motivated, curious, and critical thinker Collaborative mindset with strong independent research abilities Commitment to the highest ethical standards

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance. RESPONSIBILITIES Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas. Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization. Maintaining and improving portfolio trading in production environments. REQUIREMENTS Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline. 2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus. Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning. Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas. Ability to work both independently and collaboratively within a team. Commitment to the highest ethical standards.

About the Team Our Data Science team is the Avengers to Meesho’s S.H.I.E.L.D 🛡️. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. We’ve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. About the Role As a Principal Data Scientist in our AdTech team, you’ll drive innovation in our advertising platform using advanced machine learning and statistical methods. You’ll tackle complex problems in real-time bidding, ad ranking optimization, budget efficiency, and performance measurement that directly impact our business’s bottom line. This role requires technical excellence and business acumen and you’ll collaborate with cross-functional teams to transform data insights into actionable strategies that enhance our advertising ecosystem. What you will do Design and develop sophisticated bidding, budget pacing and other algorithms that optimize ad spend or ROI. Create frameworks and experimental design to measure ad effectiveness and ROI. Collaborate with product and engineering teams to translate business requirements into efficient AI/ML solutions. Communicate long-term roadmap, insights and recommendations to tech and business leadership. Mentor junior data scientists and provide technical guidance. Lead research initiatives in machine learning, auction theory and advertising technology. What you will need B.Tech in Computer Science, Machine Learning, or a related field with at least 6+ years of experience in AI/ML research. Experience in auction theory, predictive modelling, causal inference, and reinforcement learning. Expertise in PyTorch or TensorFlow, and proficiency in Python as we

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies. Job Description Develop systematic trading models across FX, commodities, fixed income, and equity markets Alpha idea generation, backtesting, and implementation Assist in building, maintenance, and continual improvement of production and trading environments Evaluate new datasets for alpha potential Improve existing strategies and portfolio optimization Execution monitoring Be a core contributor to growing the investment process and research infrastructure of the team Desirable Candidates Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus Experience in quantitative trading, ideally in FX or futures Experience with alpha research, portfolio construction and optimization Experience building statistical/technical, fundamental, and data driven signals Experience synthesizing predictive signals for both cross-sectional and time-series models Strong experience with data exploration, dimension reduction, and feature engineering Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity Experience managing and running risk is a strong plus Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc. Creative mindset Strong time management abi

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Stripe Infrastructure is responsible for the reliability, scale, performance, and cost of Stripe's systems and the productivity and sentiment of Stripe's people. You may work on a wide variety of critical business areas including: Core Infrastructure—We're the home for Stripe's critical tier0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency, and scalability of these systems. Developer Infrastructure—We're responsible for the productivity of all developers at Stripe. Ensure Stripe's engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models. Data Infrastructure—We're responsible for offering data serving infrastructure spanning across data warehouse analytics, streaming analytics, and search capabilities. The stack is supported by a collection of internally developed large-scale distributed services and several popular open-source technologies like Trino/Presto, Apache Pinot, Hive Metastore, ElasticSearch etc. The systems we own support all of the data serving needs of high-scale services and thousands of individual Stripes across the company. Admin Platform—We empower Stripes to quickly

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: We are looking for Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs! Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures. Responsibilities: Designing and implementing from scratch new information architecture strategies Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data Designing and evaluating advanced agentic search capabilities. You may be a good fit if you: Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using Have good machine learning research experience Have experience developing software that utilizes Large Language Models such as Claude Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to partner with world-class ML researchers to develop new LLM capabilities Care about the societal impacts of your work Have clear written and verbal communication Strong candidates will also have experience with: Collaborating with product teams to quickly prototype and deliver innovative solutions Building complex agentic systems that utilize LLMs Developing scalable d

Junior Data Scientist The Wiley Edge banking team is currently seeking a Data Scientist to work across the Front Office Trading, Risk & Regulatory Compliance Trade Analytics group, using Machine Learning and Data Analytics techniques to design and develop complex data models for client and trading analytics across their Fixed Income and FX offerings. You will be supporting the transformation from traditional controls monitoring to “on-screen” data driven monitoring and analytical solutions. Tools: Python (pandas, numpy) Machine Learning Algorithms / Natural Language Processing (NLP) AI / Robotics Predictive Analysis Good grasp of ML Algorithms Starting Salary: CA$85,000 per annum Junior Data Scientist

Who we are ? Artefact is a new generation of a data service provider, specialising in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 1000+ client base around the globe. We have 850 employees across 20 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client. Over the last few years, Data Science at Artefact Morocco has skyrocketed in terms of novel projects coupled with a growing diverse team. We tackle use cases that bring business value and serve different countries. Our area of expertise involves Applied Mathematics & Statistics for Machine Learning and Deep Learning, with a recently strong focus on Generative AI. Responsibilities : In addition to the core Data Science and ML Engineering Team, you will work with different stakeholders to: Qualify the feasibility of Use Cases, translating business challenges into technical formulations Define the business and statistical hypothesis, and build the solution followed by testing and validation For those Use Cases that are validated, you will help develop a production-ready solution. When consulted on a business challenge, you propose adequate AI or machine learning options to address this need. You act as an expert on the best algorithm to c

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience. Lead the design, implementation, and operation of cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deplo

A one-of-a-kind international company operating on the cutting edge of technology. The company has risen to prominence in the HFT (High-frequency trading) industry in recent years, having built one of the greatest teams of developers and data scientists on the market, including a great machine learning expert and top-level data scientist as the company's founder. Our trading activities span across various platforms worldwide, encompassing both traditional and cryptocurrency markets. We are seeking a Quantitative Researcher . The one who embodies intelligence, calmness, and composure. We have a lot of financial data, robust infrastructure, and a highly skilled professional team. WHAT YOU’LL BE DOING: Operate automated latency-sensitive trading systems Monitor the systems’ executions and open positions Adjust system parameters based on market conditions Suggest automation and improvements to the systems Communicate relevant news, market events, and system behavior to team members Stay current with system functionality WHAT WE LOOK FOR IN YOU: 3+ years of algorithmic trading experience A proven track record in the last 2-3 years Having your own trading strategies/ideas 1+ years experience in Python Performs well in a remote/hybrid team with variable, project-based responsibilities NICE-TO-HAVE: Experience with international HFT companies and hedge funds Performance in any quantitative field or contest (hackathons, Olympiads, academic contests, etc.) WHY SHOULD YOU JOIN OUR TEAM? Great challenges with fast feedback loops A welcoming group of highly qualified international professionals Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment Cutting-edge hardware and technology Work remotely from anywhere in the world Access any of our global offices anytime Flexible schedule 40 paid days off Competitive salary and performance-based bonuses

Perplexity is looking for experienced Generalist Software Engineers to join our Perplexity and Comet application teams. Our team is reshaping knowledge work through our high-impact desktop and Comet apps. The ideal candidate should have strong programming skills and multiple years of experience shipping high-quality, production software. Our stack spans several different skillsets, including Rust, Kotlin, Swift, Typescript, Chromium and Perplexity’s core AI stack. We have found that our strongest engineers are capable of working across multiple codebases and ramping up quickly, and we expect the same high bar for candidates. Responsibilities Work closely with product teams to implement novel mobile experiences. Work closely with design teams to design fast and intuitive UI. Utilize Perplexity Computer and other Agentic coding tools to accelerate development. Collaborate with data science and machine learning teams to instrument, analyze, and improve the end-to-end experience. Work with infrastructure and QA teams on deployment processes, including testing, release, and monitoring. Requirements 4+ years industry experience Experience in shipping high-quality native applications Architecture experience in writing code understandable by both agents and humans Deep understanding of app performance Ability to own projects and surfaces, and to push them forward proactively

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Design, implement, and operate cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deploy them efficiently in our robotaxi. Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Design, implement, and operate cutting-edge ML training performance optimization techniques — distributed training (data/tensor/pipeline parallelism), mixed-precision, gradient checkpointing, and GPU kernels — to scale our VLM, VLA, and Foundational models training efficiency. <