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Location: Yanbu, Saudi Arabia Eram Talent, a leading talent acquisition company in the Oil & Energy sector, We are seeking an experienced Process Engineer (Refinery) to be stationed at YASREF refinery. The ideal candidate will provide on-site technical support, troubleshooting, and optimization for refinery process units, ensuring safe, efficient, and reliable operations. Key Responsibilities Provide expert-level process engineering support for refinery operations. Monitor plant performance and recommend improvements to optimize efficiency, reliability, and safety. Troubleshoot operational issues and provide immediate technical solutions. Support plant modifications, debottlenecking, and process optimization initiatives. Review and validate process design, simulation, and operational data. Coordinate with operations, maintenance, and technical teams to resolve process-related challenges. Ensure compliance with safety standards, environmental regulations, and company procedures. Participate in shutdowns, startups, and commissioning activities when required. Requirements Minimum Requirements Bachelor’s Degree in Chemical Engineering or related field. Minimum 10+ years of experience in refinery process engineering roles. Strong experience in refinery operations and technical support. Technical Expertise (Mandatory) Must have experience in at least one of the following refinery process units: Two Stage Hydrocracking LPG Olefin Saturation Mercaptan Removal Delayed Coking OR strong experience in the following areas: Refinery Process Simulation Relief Load & Flare System Analysis Process Hydraulics Calculations Fired Heaters Design & Operation Refinery Real-Time Optimization (RTO) Required Skills Strong analytical and problem-solving abilities. Expertise in process simulation tools (e.g., Aspen HYSYS, UniSim). In-depth understanding of refinery operations and safety standards. Excellent communication and coordination skills. Ability to work in a fast-paced operational environment.

Location: Europe; United States Workplace: Remote ABOUT CANTINA: Cantina is a new social platform founded by Sean Parker with the most advanced AI character creator. Our bots are lifelike, social creatures that can interact wherever people are online—across voice, video, and text. Create yourself, imagine someone new, or choose from thousands of characters to share infinitely scalable, personalized content and seamless group chat. If you’re excited about how AI can shape creativity and social interaction, come help us build what’s next.   ABOUT THE ROLE: We’re looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech systems end-to-end—from data specs through production inference. You’ll drive the model ↔ data ↔ eval flywheel for VC and adjacent tasks (controllable TTS, voice design and more), partnering closely with research, data, and infra to ship fast, reliable, and cost-aware models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. You will thrive in this role if you: - See research and engineering as two sides of the same coin and enjoy owning work end-to-end. - Are results-oriented, flexible, and willing to pick up whatever moves the needle. - Like collaborating closely with infra, data, and product to ship measurable improvements. - Enjoy designing experiments, listening tests, and metrics that correlate with user-perceived quality. - Eager to learn every-day, find and solve unique large-scale problems. WHAT YOU’LL DO: - Model Building: Architect, implement, pre-train, fine-tune, and post-train/alignment (e.g., GRPO/DPO) for large-scale speech models. - Experimental Design: Design, run, and analyze scientific experiments to advance our understanding of the models. - Tool Development: Develop and improve dev tooling to enhance team productivity. - Full-Stack Contribution: Contribute to the entire stack, from low-level optimizations to high-level model design. - Data Ownership: Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies. - Rigorous Evaluation: Design automated objective/subjective evaluations—listening tests, SV/WER/ASR-based metrics, robustness & bias checks, and red-team studies. - Pipeline Delivery: Harden the training → evaluation → inference pipeline; profile latency, memory, and cost; and meet production SLAs with robust monitoring and rollback. - Safety & Responsibility: Contribute to safety/consent guardrails and to misuse/abuse mitigation for responsible speech technology.   WHAT YOU’LL BRING: - Exceptional research/development experience with large-scale audio models (>8B parameters, >500k hours of data). - Deep hands-on experience with diffusion and/or flow-matching transformers, including practical knowledge of samplers, schedules, conditioning mechanisms, and distillation. - Deep hands-on experience training audio VAEs, neural audio codecs, and vocoders latent/tokenizer design, reconstruction and perceptual objectives, adversarial training. - Strong experience with multi-node, multi-GPU distributed training (FSDP/DeepSpeed or equivalent). - Strong software engineering skills with a proven track record of building complex systems. - Strong with PyTorch and performance work (profiling, CUDA/Triton/C++ as needed) and writing reliable production-quality code. - Shipped large-scale speech/audio or multimodal generative models to production. - Background in working with large-scale ML data, and the ability to iterate on data and triangulate quality using both subjective and objective signals. - Experience with voice cloning, speech control/steerability, or expressive speech generation. - Notable publications and/or open-source contributions in speech/audio/ML. COMPENSATION: When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.   BENEFITS FOR U.S.-BASED ROLES: - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!

Location: Palo Alto Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE This role focuses on building and operating the end-to-end execution, training, and data infrastructure that powers Mistral’s agentic models and coding assistants. You will be a core contributor to our agent research stack: designing scalable systems for synthetic data generation, building ultra-fast training and RL execution environments, and maintaining high-throughput execution engines. You will tackle the engineering challenges at every step of the agent lifecycle: from orchestrating 1M+ concurrent and short-lived sandboxes for untrusted code execution to optimizing agent training codebases, distributed trajectory collection pipelines, and dataset processing workflows across massive hybrid and multi-cloud clusters. WHAT YOU WILL DO - Large-Scale Sandboxing Infrastructure: Design, deploy, and operate our high-throughput sandboxing platform, executing LLM-generated untrusted code across over 1 million isolated environments concurrently for model evaluation and interactive RL environments. - Agent Data Generation Pipelines: Architect and scale high-throughput pipelines for synthetic code generation, agent trajectories, rollouts, and self-play data collection to power post-training and RL loops. - Training Codebase & Systems Optimization: Optimize agent training codebases and distributed execution runtimes (PyTorch, Ray, SLURM/Kubernetes) to minimize multi-step rollout overhead, improve GPU utilization, and eliminate scaling bottlenecks. - Low-Latency Orchestration & Warm Pooling: Reduce sandbox cold-start times to sub-second levels using container warm pools, snapshot/restore technology (e.g., CRIU, microVMs), and optimized image delivery layers across hybrid clusters. - Multi-Cluster Queueing & Resource Allocation: Implement Kubernetes-native custom controllers, CRDs, and queuing systems to dynamically route short-lived evaluation, synthetic data, and agent execution tasks across diverse hardware fleets. - Isolation, Security & Security Boundary: Ensure strict multi-tenant network and process isolation for untrusted agent code using container/sandboxing runtimes (e.g., gVisor, Firecracker) and default-deny network postures. - Operational Excellence: Maintain high availability, telemetry, and automated self-healing across millions of transient jobs while participating in on-call rotations for critical agent training and execution pipelines. WHAT WE'RE LOOKING FOR - 4+ years of experience in Systems Engineering, Distributed Systems, Cloud Infrastructure, or MLOps supporting LLM/RL workloads. - Data & Pipeline Engineering: Proven experience building high-throughput data processing and generation pipelines for large-scale datasets (e.g., Ray, Spark, custom distributed queues). - Deep experience with Kubernetes & Container Tech: Strong expertise writing custom K8s operators/controllers, managing Linux cgroups/namespaces, and optimizing Docker image layers and distribution systems. - High-Performance Software Engineering: Advanced proficiency in Python, Go, C++ or Rust, with a track record of profiling and optimizing high-performance ML or backend systems codebases. - Sandboxing & Isolation Technologies: Hands-on experience with lightweight virtualization, container runtimes, or WASM (e.g., Docker, gVisor, Firecracker). - Queueing & Scheduling: Deep familiarity with task queue systems, resource schedulers, and low-latency queuing architectures for high-volume, short-lived workloads. - Comfort with Ambiguity: Passion for working directly alongside AI researchers to rapidly turn frontier agent ideas into scalable, production-grade infrastructure. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Americas Remote Hi, I'm Paul, VP of Engineering at Customer.io . We're always looking for thoughtful, driven Engineering Managers to add to our org. Some of our teams are building customer-facing product and workflows; others keep our distributed systems reliable, observable, and ready to scale. Whichever kind of problem energizes you, if you lead people well, hold a high technical bar, and drive work to completion without waiting to be handed a plan, we want to hear from you. About Customer.io Over 9,000 companies—from scrappy startups to global brands—use our platform to send billions of emails, push notifications, in-app messages, and SMS every day. Customer.io powers automated communication that people actually want to receive. We help teams send smarter, more relevant messages using real-time behavioral data—what people do or don't do inside a web or mobile app. Under the hood: Go, React, and AI help us ship fast and scale with confidence. What we value Ownership. You set direction and see initiatives through. You create clarity when things are murky and set the path forward rather than waiting for one to be defined, and you're motivated by impact—not just intention. You hold yourself and your team accountable to shipping, not just staying busy. Leaders who can do both. You operate at the strategic level and stay close to the technical work. You can align stakeholders on a plan and earn your engineers' respect in the same day—you don't choose between vision and execution, you hold both. A drive to execute through resistance. Competing priorities, skeptical stakeholders, tired teams—you've moved work forward anyway. You name the resistance, make the call, and own the milestones and the misses. An AI-first mindset. AI is central to how you build and how you lead your team to build. You have a real, concrete point of view on AI-native development, you use agentic tooling yourself, and you bring it into how your squad operates. A healthy skepticism for "the way things are done." You bring rigor and pragmatism. Best practices matter—but never more than forward motion. You know when to build, when to buy, and when to wait—and you're comfortable making the call with incomplete information, then adjusting as you learn. What you'll do Care deeply about our customers and their outcomes Lead your squad to deliver real customer value by owning projects end to end—from planning through delivery, quality, and follow-through Drive execution: set milestones, keep work moving through ambiguity and competing priorities, and ship in small, observable increments rather than waiting for a release window Make confident decisions when the path isn't obvious, and lead your team through them Set the operating rhythm that helps your team move fastest, rather than defaulting to ceremony for its own sake Ensure your squad's solutions are scalable, architecturally sound, flexible, and secure, with strong peer-review, QA, documentation, deployment, logging, and monitoring practices Stay close to the work—jump into design reviews, architecture calls, and incidents rather than watching from a distance Provide direct, timely, and specific coaching, and create meaningful development opportunities for your direct reports Participate in an on-call rotation as required, supporting the reliability of the systems you build Hire, onboard, and manage performance so the right people are in place to hit your squad's goals Bring an AI-native perspective—use AI tools to accelerate the team's velocity and help everyone prototype faster and ship smarter Partner across engineering and other departments to align efforts with customer success, and reach higher when our customers are having a bad day What we're looking for 3+ years managing engineers at a SaaS company (B2B or B2C), ideally early-to-mid-stage A track record of driving execution—concrete delivery outcomes with milestones, dates, and "I drove" ownership, especially in complex or fast-moving environments A strong technical background—you can hold your own in architecture conversations and design reviews, represent your squad's technical choices across the company, and you've shipped real work recently enough to stay credible Comfort operating with high autonomy and little prescribed structure—you create your own clarity and make difficult tradeoffs between competing priorities Demonstrated AI-native leadership—not just personal fluency, but bringing AI-first practices into how your team builds Experience building high-performing, inclusive, and collaborative teams Clear, concise, and direct communication, both verbal and written Compensation & Benefits We believe in transparency. Starting salary for this role is $185,000-$215,000 USD (or equivalent in local currency) depending on experience and subject to market rate adjustment. In addition to base salary, this role includes an equity grant in the form of stock options, so you share in the success you help build. We know our people are what make us great, and we're committed to taking great care of them. Our inclusive benefits package supports your well-being and growth, including 100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for you and your family . We also offer 16 weeks paid parental leave , unlimited PTO , stipends for remote work and wellness, a professional development budget, and more. See full benefits here → Our Process No gotchas, no trick questions - just a clear, human process designed to help both of us make an informed decision. Application - We review everyone with care. Recruiter Call (30 mins) - Let's chat about what you're looking for, your leadership style, and how we work. Hiring Manager Interview (60 mins) - Deep dive into your experience leading teams, your technical philosophy, and how you think about building organizations. People Partner Interview (30 mins) - Explore your leadership style, management philosophy, and approach to supporting high-performing teams with our engineering people partner. Technical Interview (60 mins) - Engage in a collaborative system design conversation focused on scaling challenges. Take-Home Assignment - Submit a short written retrospective on a project you’ve led as an Engineering Manager. Retrospective Review Call (60 mins) - We’ll use your written submission as the foundation for a deeper conversation. All final candidates will be asked to complete a background check and employment verifications as part of our pre-employment process.

Location: Latvia Workplace: Remote Location: Remote (Europe Time Zone) Start date: ASAP Language: English Team: AI ABOUT THE ROLE Our client is a European technology company operating a cloud and infrastructure platform, and we are looking for an AI Engineering Manager to lead the small, high-leverage team behind their AI product. The Engineering Manager is to lead a team of AI engineers and researchers building the systems that power an AI-enabled products and the model inference offering. You’ll manage the people and the roadmap: hiring and developing a high-caliber team, setting technical direction alongside senior ICs, and driving delivery on projects that range from applied ML features inside the products to the infrastructure that serves models in production at scale. This is a hybrid people/technical leadership role. You should be comfortable running a team day-to-day (1:1s, planning, performance, hiring) while also being comfortable enough technically to review designs, unblock research and engineering tradeoffs, and represent the team to other engineering and product leaders.   WHAT YOU'LL DO - Manage, coach, and grow a team of AI/ML engineers and researchers, including hiring, career development, and performance management. - Own delivery for AI-enabling projects across the product portfolio, translating ambiguous product and research goals into scoped, sequenced engineering plans. - Co-own the roadmap and operations of the inference offering, including reliability, latency, cost, and scaling of model serving infrastructure. - Partner with research scientists to move promising models and techniques from experimentation into production, balancing research rigor with shipping velocity. - Set and maintain engineering standards for the team: code quality, experimentation practices, evaluation methodology, on-call, and incident response for production inference systems. - Work closely with Product, Infrastructure, and Data teams to prioritize work and remove cross-team blockers. - Report on team progress, risks, and capacity to engineering leadership, and represent the team’s work in planning and roadmap discussions. - Stay current on the AI/ML and inference landscape (models, serving frameworks, hardware) and bring relevant developments back to the team’s technical strategy. WHAT WE'RE LOOKING FOR - 7+ years of experience in a technical leadership or engineering management role (AI/ML teams preferred), plus a strong prior track record as a hands-on engineer or researcher. - Proven experience building and operating AI/ML platform or inference infrastructure in production (model serving, GPU workloads, latency and cost optimization) - Working knowledge of the AI/ML lifecycle: model training or fine-tuning, evaluation, and production deployment. - Experience with, or strong technical fluency in, model inference and serving infrastructure (e.g., GPU scheduling, batching, quantization, latency/throughput tradeoffs, serving frameworks such as vLLM, Triton, or similar). - Demonstrated ability to manage both researchers and engineers, who often have different working styles, timelines, and definitions of “done.” - Strong judgment on scoping and sequencing ambiguous, research-adjacent projects into shippable increments. - Excellent communication skills; able to translate technical tradeoffs for both engineers and non-technical stakeholders. - Experience owning production systems, including reliability and incident response, is a plus. WHY THIS ROLE MATTERS FOR YOU - Own a product, not a component: Lead the team behind the company's AI product and shape the capabilities the wider business builds on - High leverage, small team: With three engineers, your technical and strategic decisions translate directly into what ships - Grow as a leader: Manage, mentor, and inspire a talented team while influencing strategic technical decisions - Stay hands-on: Balance leadership with coding in a modern, high-scale AI platform environment - Work with cutting-edge technology: Deepen your expertise in LLMs, inference infrastructure, GPU compute, and distributed systems at scale - Drive platform evolution: Directly impact architecture, reliability, and AI quality across the organization - Collaborate across teams: Work closely with Product, Infrastructure, Security, and Backend teams, expanding your cross-functional expertise - Remote-first flexibility: Enjoy a fully remote role while aligning with the European time zone Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

Location: Türkiye Workplace: Remote Location: Remote (Europe Time Zone) Start date: ASAP Language: English Team: AI ABOUT THE ROLE Our client is a European technology company operating a cloud and infrastructure platform, and we are looking for an AI Engineering Manager to lead the small, high-leverage team behind their AI product. The Engineering Manager is to lead a team of AI engineers and researchers building the systems that power an AI-enabled products and the model inference offering. You’ll manage the people and the roadmap: hiring and developing a high-caliber team, setting technical direction alongside senior ICs, and driving delivery on projects that range from applied ML features inside the products to the infrastructure that serves models in production at scale. This is a hybrid people/technical leadership role. You should be comfortable running a team day-to-day (1:1s, planning, performance, hiring) while also being comfortable enough technically to review designs, unblock research and engineering tradeoffs, and represent the team to other engineering and product leaders.   WHAT YOU'LL DO - Manage, coach, and grow a team of AI/ML engineers and researchers, including hiring, career development, and performance management. - Own delivery for AI-enabling projects across the product portfolio, translating ambiguous product and research goals into scoped, sequenced engineering plans. - Co-own the roadmap and operations of the inference offering, including reliability, latency, cost, and scaling of model serving infrastructure. - Partner with research scientists to move promising models and techniques from experimentation into production, balancing research rigor with shipping velocity. - Set and maintain engineering standards for the team: code quality, experimentation practices, evaluation methodology, on-call, and incident response for production inference systems. - Work closely with Product, Infrastructure, and Data teams to prioritize work and remove cross-team blockers. - Report on team progress, risks, and capacity to engineering leadership, and represent the team’s work in planning and roadmap discussions. - Stay current on the AI/ML and inference landscape (models, serving frameworks, hardware) and bring relevant developments back to the team’s technical strategy. WHAT WE'RE LOOKING FOR - 7+ years of experience in a technical leadership or engineering management role (AI/ML teams preferred), plus a strong prior track record as a hands-on engineer or researcher. - Proven experience building and operating AI/ML platform or inference infrastructure in production (model serving, GPU workloads, latency and cost optimization) - Working knowledge of the AI/ML lifecycle: model training or fine-tuning, evaluation, and production deployment. - Experience with, or strong technical fluency in, model inference and serving infrastructure (e.g., GPU scheduling, batching, quantization, latency/throughput tradeoffs, serving frameworks such as vLLM, Triton, or similar). - Demonstrated ability to manage both researchers and engineers, who often have different working styles, timelines, and definitions of “done.” - Strong judgment on scoping and sequencing ambiguous, research-adjacent projects into shippable increments. - Excellent communication skills; able to translate technical tradeoffs for both engineers and non-technical stakeholders. - Experience owning production systems, including reliability and incident response, is a plus. WHY THIS ROLE MATTERS FOR YOU - Own a product, not a component: Lead the team behind the company's AI product and shape the capabilities the wider business builds on - High leverage, small team: With three engineers, your technical and strategic decisions translate directly into what ships - Grow as a leader: Manage, mentor, and inspire a talented team while influencing strategic technical decisions - Stay hands-on: Balance leadership with coding in a modern, high-scale AI platform environment - Work with cutting-edge technology: Deepen your expertise in LLMs, inference infrastructure, GPU compute, and distributed systems at scale - Drive platform evolution: Directly impact architecture, reliability, and AI quality across the organization - Collaborate across teams: Work closely with Product, Infrastructure, Security, and Backend teams, expanding your cross-functional expertise - Remote-first flexibility: Enjoy a fully remote role while aligning with the European time zone Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

Location: Armenia Workplace: Remote Location: Remote (Europe Time Zone) Start date: ASAP Language: English Team: AI ABOUT THE ROLE Our client is a European technology company operating a cloud and infrastructure platform, and we are looking for an AI Engineering Manager to lead the small, high-leverage team behind their AI product. The Engineering Manager is to lead a team of AI engineers and researchers building the systems that power an AI-enabled products and the model inference offering. You’ll manage the people and the roadmap: hiring and developing a high-caliber team, setting technical direction alongside senior ICs, and driving delivery on projects that range from applied ML features inside the products to the infrastructure that serves models in production at scale. This is a hybrid people/technical leadership role. You should be comfortable running a team day-to-day (1:1s, planning, performance, hiring) while also being comfortable enough technically to review designs, unblock research and engineering tradeoffs, and represent the team to other engineering and product leaders. WHAT YOU'LL DO - Manage, coach, and grow a team of AI/ML engineers and researchers, including hiring, career development, and performance management. - Own delivery for AI-enabling projects across the product portfolio, translating ambiguous product and research goals into scoped, sequenced engineering plans. - Co-own the roadmap and operations of the inference offering, including reliability, latency, cost, and scaling of model serving infrastructure. - Partner with research scientists to move promising models and techniques from experimentation into production, balancing research rigor with shipping velocity. - Set and maintain engineering standards for the team: code quality, experimentation practices, evaluation methodology, on-call, and incident response for production inference systems. - Work closely with Product, Infrastructure, and Data teams to prioritize work and remove cross-team blockers. - Report on team progress, risks, and capacity to engineering leadership, and represent the team’s work in planning and roadmap discussions. - Stay current on the AI/ML and inference landscape (models, serving frameworks, hardware) and bring relevant developments back to the team’s technical strategy. WHAT WE'RE LOOKING FOR - 7+ years of experience in a technical leadership or engineering management role (AI/ML teams preferred), plus a strong prior track record as a hands-on engineer or researcher. - Proven experience building and operating AI/ML platform or inference infrastructure in production (model serving, GPU workloads, latency and cost optimization) - Working knowledge of the AI/ML lifecycle: model training or fine-tuning, evaluation, and production deployment. - Experience with, or strong technical fluency in, model inference and serving infrastructure (e.g., GPU scheduling, batching, quantization, latency/throughput tradeoffs, serving frameworks such as vLLM, Triton, or similar). - Demonstrated ability to manage both researchers and engineers, who often have different working styles, timelines, and definitions of “done.” - Strong judgment on scoping and sequencing ambiguous, research-adjacent projects into shippable increments. - Excellent communication skills; able to translate technical tradeoffs for both engineers and non-technical stakeholders. - Experience owning production systems, including reliability and incident response, is a plus. WHY THIS ROLE MATTERS FOR YOU - Own a product, not a component: Lead the team behind the company's AI product and shape the capabilities the wider business builds on - High leverage, small team: With three engineers, your technical and strategic decisions translate directly into what ships - Grow as a leader: Manage, mentor, and inspire a talented team while influencing strategic technical decisions - Stay hands-on: Balance leadership with coding in a modern, high-scale AI platform environment - Work with cutting-edge technology: Deepen your expertise in LLMs, inference infrastructure, GPU compute, and distributed systems at scale - Drive platform evolution: Directly impact architecture, reliability, and AI quality across the organization - Collaborate across teams: Work closely with Product, Infrastructure, Security, and Backend teams, expanding your cross-functional expertise - Remote-first flexibility: Enjoy a fully remote role while aligning with the European time zone Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

Location: Romania Workplace: Remote Location: Remote (Europe Time Zone) Start date: ASAP Language: English Team: AI ABOUT THE ROLE Our client is a European technology company operating a cloud and infrastructure platform, and we are looking for an AI Engineering Manager to lead the small, high-leverage team behind their AI product. The Engineering Manager is to lead a team of AI engineers and researchers building the systems that power an AI-enabled products and the model inference offering. You’ll manage the people and the roadmap: hiring and developing a high-caliber team, setting technical direction alongside senior ICs, and driving delivery on projects that range from applied ML features inside the products to the infrastructure that serves models in production at scale. This is a hybrid people/technical leadership role. You should be comfortable running a team day-to-day (1:1s, planning, performance, hiring) while also being comfortable enough technically to review designs, unblock research and engineering tradeoffs, and represent the team to other engineering and product leaders.   WHAT YOU'LL DO - Manage, coach, and grow a team of AI/ML engineers and researchers, including hiring, career development, and performance management. - Own delivery for AI-enabling projects across the product portfolio, translating ambiguous product and research goals into scoped, sequenced engineering plans. - Co-own the roadmap and operations of the inference offering, including reliability, latency, cost, and scaling of model serving infrastructure. - Partner with research scientists to move promising models and techniques from experimentation into production, balancing research rigor with shipping velocity. - Set and maintain engineering standards for the team: code quality, experimentation practices, evaluation methodology, on-call, and incident response for production inference systems. - Work closely with Product, Infrastructure, and Data teams to prioritize work and remove cross-team blockers. - Report on team progress, risks, and capacity to engineering leadership, and represent the team’s work in planning and roadmap discussions. - Stay current on the AI/ML and inference landscape (models, serving frameworks, hardware) and bring relevant developments back to the team’s technical strategy. WHAT WE'RE LOOKING FOR - 7+ years of experience in a technical leadership or engineering management role (AI/ML teams preferred), plus a strong prior track record as a hands-on engineer or researcher. - Proven experience building and operating AI/ML platform or inference infrastructure in production (model serving, GPU workloads, latency and cost optimization) - Working knowledge of the AI/ML lifecycle: model training or fine-tuning, evaluation, and production deployment. - Experience with, or strong technical fluency in, model inference and serving infrastructure (e.g., GPU scheduling, batching, quantization, latency/throughput tradeoffs, serving frameworks such as vLLM, Triton, or similar). - Demonstrated ability to manage both researchers and engineers, who often have different working styles, timelines, and definitions of “done.” - Strong judgment on scoping and sequencing ambiguous, research-adjacent projects into shippable increments. - Excellent communication skills; able to translate technical tradeoffs for both engineers and non-technical stakeholders. - Experience owning production systems, including reliability and incident response, is a plus. WHY THIS ROLE MATTERS FOR YOU - Own a product, not a component: Lead the team behind the company's AI product and shape the capabilities the wider business builds on - High leverage, small team: With three engineers, your technical and strategic decisions translate directly into what ships - Grow as a leader: Manage, mentor, and inspire a talented team while influencing strategic technical decisions - Stay hands-on: Balance leadership with coding in a modern, high-scale AI platform environment - Work with cutting-edge technology: Deepen your expertise in LLMs, inference infrastructure, GPU compute, and distributed systems at scale - Drive platform evolution: Directly impact architecture, reliability, and AI quality across the organization - Collaborate across teams: Work closely with Product, Infrastructure, Security, and Backend teams, expanding your cross-functional expertise - Remote-first flexibility: Enjoy a fully remote role while aligning with the European time zone Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

Location: Budapest The Wow This role sits at the heart of our real-time data platform, empowering teams to build, deploy, and scale data products that drive critical business decisions and customer experiences. You will design, develop, and operate the core platform capabilities that power streaming data pipelines, event-driven applications, and self-service data products. Working at the intersection of software engineering and data engineering, you will create scalable frameworks, tooling, and developer experiences that enable our teams to deliver reliable solutions with speed and confidence. A taster of what you will be involved with: Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing. Develop and maintain the platform's core capabilities, such as orchestration, data quality validation, and schema management tools. Evolve the platform's architecture to incorporate new technologies that improve scalability, reliability, and cost-effectiveness. Collaborate with Data DevOps Engineers to ensure platform features are automated, observable, and deployed via CI/CD. Act as a key contributor to the platform's roadmap, identifying and prioritizing features that unlock the most value for its users. What we are looking for: Must haves: University Degree in Computer Science, Engineering or equivalent. At least 3 years of hands-on experience building and operating real-time or event-driven data platforms and streaming applications. Strong software engineering fundamentals, with experience in a language like Python, Scala or Java. Experience building reusable frameworks, libraries, or internal tools. Deep knowledge of SQL and data integration patterns. Experience in modern cloud database technologies such as Snowflake or Redshift are considered an asset. Experience with data streaming technologies such as Kafka is a must. Strong experience building distributed data processing workloads using Apache Spark (PySpark and/or Scala). Hands-on experience designing and operating event-driven architectures on AWS, including services such as MSK, Kinesis Data Streams, EKS, EMR, Lambda, and EventBridge. Experience in NoSQL databases such as  HBase, Cassandra, and DynamoDB. Excellent verbal and writing English communication skills. Nice to have: Familiarity with real time reporting tools like Grafana or Datadog Familiarity with Data Modelling Concepts like Inmon, Kimball and Data Vault Knowledge AWS services like Glue, Lambda, Step Functions and S3 Experience with orchestrating data pipelines using tools like Airflow. Experience building or managing APIs and microservices. Familiarity with infrastructure scripting like Terraform and CI/CD practices. What we offer Fitness-wellness allowance 🧗‍♂️ Company mobile phone for private use with 100 GB 📱 Annual HUF devaluation compensation 💡 Hybrid model: 3 days in the office 🏢 & 2 days from home 🏠 Private Health Insurance 🩺 Career development 📈 Technical and soft-skill training opportunities 🎓 Breakfast, fruits & lunch 🍎 Team building events 🥳 Challenge accepted? By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

Location: Malta The Wow This role sits at the heart of our real-time data platform, empowering teams to build, deploy, and scale data products that drive critical business decisions and customer experiences. You will design, develop, and operate the core platform capabilities that power streaming data pipelines, event-driven applications, and self-service data products. Working at the intersection of software engineering and data engineering, you will create scalable frameworks, tooling, and developer experiences that enable our teams to deliver reliable solutions with speed and confidence. A taster of what you will be involved with: Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing. Develop and maintain the platform's core capabilities, such as orchestration, data quality validation, and schema management tools. Evolve the platform's architecture to incorporate new technologies that improve scalability, reliability, and cost-effectiveness. Collaborate with Data DevOps Engineers to ensure platform features are automated, observable, and deployed via CI/CD. Act as a key contributor to the platform's roadmap, identifying and prioritizing features that unlock the most value for its users. What we are looking for: Must haves: University Degree in Computer Science, Engineering or equivalent. At least 3 years of hands-on experience building and operating real-time or event-driven data platforms and streaming applications. Strong software engineering fundamentals, with experience in a language like Python, Scala or Java. Experience building reusable frameworks, libraries, or internal tools. Deep knowledge of SQL and data integration patterns. Experience in modern cloud database technologies such as Snowflake or Redshift are considered an asset. Experience with data streaming technologies such as Kafka is a must. Strong experience building distributed data processing workloads using Apache Spark (PySpark and/or Scala). Hands-on experience designing and operating event-driven architectures on AWS, including services such as MSK, Kinesis Data Streams, EKS, EMR, Lambda, and EventBridge. Experience in NoSQL databases such as  HBase, Cassandra, and DynamoDB. Excellent verbal and writing English communication skills. Nice to have: Familiarity with real time reporting tools like Grafana or Datadog Familiarity with Data Modelling Concepts like Inmon, Kimball and Data Vault Knowledge AWS services like Glue, Lambda, Step Functions and S3 Experience with orchestrating data pipelines using tools like Airflow. Experience building or managing APIs and microservices. Familiarity with infrastructure scripting like Terraform and CI/CD practices. What we offer Much like riding a rollercoaster, sometimes life at Betsson can be lightning fast with twists and turns but always FUN! Then again, what else would you expect from a business 75% millennial and 1700 strong, spread across 7 offices with 900 based out of our Malta HQ alone! We recognise it may not be for the faint-hearted, but if you’re a go-getter, initiator and adrenaline junkie, always striving to push the boundaries and challenge yourself, then you’ll fit right in. Challenge accepted? By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

Задачи: — Мониторинг сервисов и оперативное реагирование на инциденты. — Диагностика и устранение технических неисправностей. — Анализ логов и поиск причин возникновения ошибок. — Выполнение регламентных технических работ. — Взаимодействие с командами разработки, DevOps и телеком-направлением. Требования: — Уверенное владение Linux и работа в командной строке. — Базовые знания сетевых технологий (TCP/IP, DNS, VPN, HTTP/HTTPS). — Умение работать с SQL (SELECT, JOIN, UPDATE). — Базовые знания Docker. — Умение анализировать логи приложений и операционной системы. — Английский язык на уровне чтения технической документации. Будет плюсом: — Опыт работы с Grafana, Zabbix, Prometheus. — Знание Redis. — Опыт работы с Git. — Опыт работы с Asterisk, FreeSWITCH или другими VoIP-решениями. — Понимание CI/CD и опыт сопровождения SaaS-продуктов. Условия: — Работа в международной AI-компании. — Сменный график работы. — Комфортный офис в Алматы. — Бесплатные обеды. — Оплата тренажерного зала. — Возможность работать с современной AI-инфраструктурой и развиваться в направлении Linux/DevOps.

Задачи: — Проектировать, строить и оптимизировать крупномасштабные ETL, стриминговые и пакетные конвейеры обработки данных. — Реализовывать и поддерживать высокопроизводительные/низколатентные хранилища данных (например, для рекомендаций в реальном времени). — Внедрять и улучшать механизмы управления данными для обеспечения качества и надежности данных. — Ускорять инновации, создавая и улучшая инфраструктуру машинного обучения, включая фреймворки для обучения, оценки и экспериментов. — Сотрудничать с менеджерами продуктов, дата-сайентистами, инженерами и аналитиками для создания положительного влияния на клиентов. — Помогать определять цели команды. — Постоянно улучшать самоорганизацию команды. Требования: — Опыт применения принципов инженерии программного обеспечения к системам управления данными. — Умение строить надежную, масштабируемую инфраструктуру данных с использованием качественного кода, а не только SQL. — Опыт не менее 3 лет в проектах по инженерии данных. — Хорошее понимание распределенных механизмов обработки данных. — Умение диагностировать и оптимизировать медленные конвейеры данных. — Опыт работы с крупномасштабной пакетной и/или потоковой обработкой (например, Spark, Hadoop, Flink, Storm, Apache Beam, Kafka). — Владение Python или Java. — Глубокое понимание распределенных баз данных, особенно высокопроизводительных/низколатентных хранилищ данных (например, DynamoDB, Cassandra, Redis). Условия: — Программа акций для сотрудников. — Скидки 40% на товары моды и красоты Zalando, 30% на Zalando Lounge, скидки у внешних партнеров. — 2 оплачиваемых дня волонтерства в год. — Гибридный режим работы с возможностью до 60% удаленной работы в неделю. — Возможность работать из-за рубежа до 30 рабочих дней в году. — 27 дней отпуска в год с начала работы. — Помощь с релокацией (по предварительной договоренности). — Семейные услуги, включая консультации и поддержку. — Опции для здоровья и благополучия (включая Gympass). — Поддержка психического здоровья и коучинг. — Возможности развития через обучающую платформу и двухразовые отзывы от коллег.

Задачи: — Проектировать, строить и оптимизировать крупномасштабные ETL, стриминговые и пакетные конвейеры обработки данных. — Реализовывать и поддерживать высокопроизводительные/низколатентные хранилища данных (например, для рекомендаций в реальном времени). — Внедрять и улучшать механизмы управления данными для обеспечения качества и надежности данных. — Ускорять инновации, создавая и улучшая инфраструктуру машинного обучения, включая фреймворки для обучения, оценки и экспериментов. — Сотрудничать с менеджерами продуктов, дата-сайентистами, инженерами и аналитиками для создания положительного влияния на клиентов. — Помогать определять цели команды. — Постоянно улучшать самоорганизацию команды. Требования: — Опыт применения принципов инженерии программного обеспечения к системам управления данными. — Умение строить надежную, масштабируемую инфраструктуру данных с использованием качественного кода, а не только SQL. — Опыт не менее 3 лет в проектах по инженерии данных. — Хорошее понимание распределенных механизмов обработки данных. — Умение диагностировать и оптимизировать медленные конвейеры данных. — Опыт работы с крупномасштабной пакетной и/или потоковой обработкой (например, Spark, Hadoop, Flink, Storm, Apache Beam, Kafka). — Владение Python или Java. — Глубокое понимание распределенных баз данных, особенно высокопроизводительных/низколатентных хранилищ данных (например, DynamoDB, Cassandra, Redis). Условия: — Программа акций для сотрудников. — Скидки 40% на товары моды и красоты Zalando, 30% на Zalando Lounge, скидки у внешних партнеров. — 2 оплачиваемых дня волонтерства в год. — Гибридный режим работы с возможностью до 60% удаленной работы в неделю. — Возможность работать из-за рубежа до 30 рабочих дней в году. — 27 дней отпуска в год с начала работы. — Помощь с релокацией (по предварительной договоренности). — Семейные услуги, включая консультации и поддержку. — Опции для здоровья и благополучия (включая Gympass). — Поддержка психического здоровья и коучинг. — Возможности развития через обучающую платформу и двухразовые отзывы от коллег.

We are a global algorithmic trading firm with an advanced technology stack, driving the full trading cycle — from market research and strategy design to algorithm development and software engineering. Our strength lies in deep market expertise and the continuous evolution of our infrastructure to stay ahead of the industry. Responsibilities: — Work through high-level business and technical requirements with the product, trading, and engineering teams, then build the resulting platform features. — Design, build, and maintain core platform components in Rust: exchange and broker gateways, data pipelines, monitoring tools, and algo trading infrastructure. — Optimize latency, throughput, and stability based on measurements and load testing. Low latency, reliability, and determinism are hard requirements. — Add observability to new components (metrics, logs, tracing, alerts, dashboards) so execution issues get caught early. — Diagnose incidents in the trading loop, find the root cause, write up the analysis, and fix the problem so it does not recur. — Ensure quality through automated (unit, integration, performance) and manual testing with QA, and maintain the test harnesses and integration suites that validate scenarios before production. — Document modules, service contracts, integration rules, and operational runbooks. — Help design and decompose features and epics, taking the product and trading side and operational risk into account. Qualifications: — 5+ years of relevant experience building low-latency, high-reliability systems. — Extensive experience in Rust. — Good understanding of computer systems and software architecture: Linux, networking, data structures and algorithms, concurrent and parallel programming, distributed computing, and performance optimization. — Strong engineering fundamentals and a preference for readable, maintainable code and sensible testing. — Takes ownership of tasks through to production and works to clear blockers, including pushing peers when needed. — Higher technical education or equivalent professional experience. Nice to have: — Familiarity with a trading domain: market data, trading protocols, operational risk. What we offer: — Remote-first: work from anywhere. — Tech-driven environment: no bureaucracy, legacy systems, or tech debt. — Growth & development: work with top talent in a fast-paced, innovation-driven culture. — Perks: medical insurance, sports benefits, home office setup, and educational support.

Location: San Francisco; New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW We’re looking for a versatile Senior Analytics Engineer focusing on Product to architect event data models that power decision-making at Harvey. With product-market fit already proven and demand surging across diverse customer segments, you’ll design clean, reliable pipelines and semantic data models that turn raw events into usable insights. As an Analytics Engineer on our team, you’ll help evolve our data stack, champion best practices in testing and documentation, and collaborate closely with product, GTM, and leadership to ensure every team can answer its own questions with confidence. If you combine engineering rigor with a love of storytelling through data we’d love to meet you. WHAT YOU'LL DO - Design and build scalable data models and pipelines using dbt to transform raw data into clean, reliable assets that power company-wide analytics and decision-making. - Define and implement a robust semantic layer (e.g. LookML/Omni/Other) that standardizes key business metrics, dimensions, and data products, ensuring self-serve capabilities for stakeholders across teams. - Partner cross-functionally with Product, GTM, Finance, and the Exec Team to deliver intuitive, consistent dashboards and analytical tools that surface business health metrics. - Establish and champion data modeling standards and best practices, guiding the organization in how to model data for accuracy, performance, usability, and long-term maintainability. - Partner with Product Managers, Engineers, and Data teams to design tracking plans for new product surfaces, ensuring events are implemented accurately, consistently, and with downstream analytics use cases in mind. - Own the product event tracking strategy, including event naming conventions, property schemas, identity resolution, sessionization, versioning, deprecation, and documentation standards. - Empower stakeholders with data by making analytical assets easily discoverable, reliable, and well-documented – turning complex datasets into actionable insights for the business. - You’ll define the structure, taxonomy, governance, and modeling patterns for product event data, ensuring that user behavior, product usage, and customer journeys are captured consistently from instrumentation through analytics-ready models. WHAT YOU HAVE - 5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field. - Deep expertise in SQL, dbt, Python, Snowflake. - Experience with modern BI tools like (Looker/Omni, or similar). - Skilled at defining core business and product metrics, uncovering insights, and resolving data inconsistencies across complex systems. - Strong familiarity with version control (GitHub), CI/CD, and modern development workflows. - Bias for action – you prefer launching usable, iterative data models that deliver immediate value over waiting for perfect solutions. - Strong communicator who can build trusted partnerships across Product, GTM, Finance, and Exec stakeholders. Comfortable working through ambiguity in fast-moving, cross-functional environments. - Balances big-picture thinking with precision in execution – knowing when to sweat the details and when to move quickly. - Experience modeling high-volume, semi-structured product event data, including JSON payloads, nested properties, user/account identifiers, sessions, funnels, cohorts, and behavioral metrics. - Experience with product analytics tools (Mixpanel, Segment, Amplitude) BONUS - Early employee at a hyper-growth startup - Experience with or knowledge of AI and LLMs - Data Engineering Experience - Experience managing data warehouse (preferably Snowflake) - Experience at world-class enterprise orgs (ex: Brex, Ramp, Stripe, Palantir) COMPENSATION $155,800 - $233,600 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES [HERE https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922]. #LI-CD1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Canada; United States Role: As a member of the Systems Engineering Department, the Platform RF/EMC Systems Engineer will provide technical expertise necessary to ensure electromagnetic compatibility (EMC) of the Platform system given the radio frequency (RF) environments of the communications payloads. Tasks: Depending on the job function, the Platform RF/EMC Systems Engineer will perform and participate in the following tasks and activities depending on the background and experience of the candidate: Perform EMC analyses and interpret unit-level EMC test reports Review communication Payload RF transmitter/receiver analyses & test results and recommend any necessary design enhancements to ensure electromagnetic compatibility with the Platform subsystems Prepare system-level EMC test plans and conduct satellite-level EMC testing Support Platform design activities related to grounding & shielding and wiring harness signal segregation & routing Troubleshoot EMC-related issues on integrated satellite and Platform Engineering Model (FlatSat) test setups Support RF/EMC aspects of systems engineering documentation including requirements specifications, statement of compliance, verification matrix and design descriptions Support various program reviews: , SRR, PDR and CDR Must haves: Bachelor’s degree in electrical or aerospace engineering 5+ years of relevant experience Strong RF and/or EMC engineering background Substantial experience with large scale system-level EMC testing Experience with unit-level EMC testing per international standards (or equivalent) methods & testing levels Systems engineering background including experience with RF, digital & analog electronic unit designs and wiring harnesses Complementary skills/knowledge: Understanding of the space environment and communication satellites Demonstrated capability to efficiently work with little to no supervision Ability to lead and/or mentor junior members of the engineering team Strong written and verbal communications skills in English, knowledge of French will be considered favorably

Location: Huntsville, AL Step into the innovative world of LG Electronics. As a global leader in technology, LG Electronics is dedicated to creating innovative solutions for a better life. Our brand promise, 'Life's Good', embodies our commitment to ensuring a happier life for all. We have a rich history spanning over six decades and a global presence in over 290 locations.  Our diverse portfolio includes Home Appliance Solutions, Media Entertainment Solutions, Vehicle Solutions, and Eco Solutions.  Our management philosophy, "Jeong-do Management," embodies our commitment to high ethical standards and transparent operations. Grounded in the principles of 'Customer-Value Creation' and 'People-Oriented Management', these values shape our corporate culture, fostering creativity, diversity, and integrity. At LG, we believe in the power of collective wisdom through an inclusive work environment.  Join us and become a part of a company that is shaping the future of technology.  At LG, we strive to make Life Good for Everyone. What we can offer : A crafted employee experience designed to foster professional growth, a focus on health & well-being and an internal community that will set you up for success. We offer an environment that enables colleagues to demonstrate their capabilities, focus on their work and create value.  At LG, you're encouraged to take a creative and individual approach to challenges with strong emphasis placed on performance and skill—and equal, merit-based opportunities across the board.  We want our colleagues to grow with our global business.  That's why we deliver sure rewards for exceptional performance and offer industry-leading benefits.  Come join the team! The Opportunity: We are looking for a highly versatile Data Scientist / AI Engineer who can work at the intersection of data science, AI engineering, internal product, operations, and business stakeholders. This role is ideal for someone who can analyze large-scale operational data, identify opportunities for automation and optimization, and build practical AI-powered tools that improve Contact Center and Voice of Customer operations. The ideal candidate is not only strong in analytics and machine learning, but also comfortable building lightweight applications, integrating AI APIs, creating dashboards, presenting ideas to stakeholders, and working closely with cross-functional teams to turn ambiguous business problems into scalable solutions. This person will support contact center operations by delivering actionable insights, automating manual workflows, improving operational efficiency, and contributing to reusable AI frameworks that can be scaled across teams and use cases. A key focus of this role is to leverage AI and contact center call data to identify agent performance gaps, customer pain points, process issues, and quality risks, and translate those findings into practical corrective actions and coaching recommendations for agents and supervisors. The candidate will be expected to go beyond reporting and insight generation by helping operational teams take measurable actions that improve agent behavior, call quality, customer experience, and overall contact center performance. Responsibilities: Analyze contact center, customer, operational, and Voice of Customer data to identify trends, monitor KPIs, and provide actionable insights. Build and automate dashboards, reports, and analytics workflows using Python, SQL, BigQuery, Looker, and related tools. Develop AI, automation, and optimization solutions to improve contact center performance, agent productivity, quality monitoring, and customer experience. Build internal tools and prototypes using Python, FastAPI, APIs, and front-end technologies as needed. Analyze call transcripts, QA data, CRM notes, and customer feedback to identify process gaps, coaching opportunities, and improvement areas. Partner with business and technical stakeholders to define requirements, validate solutions, and drive adoption. Prepare presentations, business cases, and executive updates for analytics, AI, and automation initiatives. Education / Experience (Requirements): Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field. Strong experience with Python, SQL, data analysis, automation, and dashboard/report development. Experience with BI tools such as Looker, Tableau, Power BI, or similar platforms. Knowledge of machine learning, AI APIs, LLMs, prompt engineering, or generative AI tools. Ability to build internal tools or prototypes using FastAPI, Flask, JavaScript, HTML/CSS, or similar technologies. Strong analytical, communication, and presentation skills with the ability to translate data into business recommendations. Ability to manage multiple priorities and work independently in a fast-paced environment. Preferred Qualifications: Experience with contact center, customer service, CRM, telephony, QA, chatbot/IVR, or Voice of Customer data. Familiarity with contact center KPIs such as AHT, SLA, FCR, CSAT, NPS, backlog, and agent utilization. Experience with cloud platforms, AI agents, RAG, internal copilots, workflow automation, MLOps, Git, Docker, or CI/CD. Experience with forecasting, optimization, workforce planning, or process improvement. Technical Skills Python, SQL, BigQuery, Looker, Excel, Java, FastAPI, Flask, REST APIs, HTML/CSS, JavaScript, LLMs, GPT APIs, NLP, machine learning, GCP/AWS, Git, Docker. #LI-TF1 Recruiting Range $90,000 — $100,000 USD Benefits Offered Full-Time Employees: No-cost employee premiums for you and your eligible dependents for competitive medical, dental, vision and prescription benefits. Auto enrollment with immediate vesting of competitive company matching contributions in a 401(k) Retirement Savings Plan with several investment options. Generous Paid Time Off program that includes company holidays and a combined bank of paid sick and vacation time. Performance based Short-Term Incentives (varies by role). Access to confidential mental health resources to help you and your loved ones improve your quality of life. Personal fitness goal incentives. Family orientated benefits such as paid parental leave and support for families raising children with learning, social, behavioral challenges, or developmental disabilities. Group Rate Life and Disability Insurance. Benefits Offered Temporary/Contractors: Eligible for the relevant benefit programs offered through our partner agencies. Privacy Notice to California Applicants Applicants who need assistance or a reasonable accommodation during the hiring process may contact our team by phone at: 973-477-7090 or support@lg4me.freshdesk.com. This email and phone number will only reply to accommodation requests and is not intended for general employment inquiries. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. In addition to the above, LG believes that pay transparency is a key part of diversity, equity, and inclusion. Our salary ranges take into account many factors in making compensation decisions including but not limited to skillset, experience, licensure, certifications, internal equity, and other business needs. While we consider geographic pay differentials in final offers, because we operate in many geographies where applicable, the salary range listed may not reflect all geographic differentials applied .

Location: Chicago, IL; Dallas, TX; Denver, CO; Lincoln, NE; Minnesota - Remote; Oklahoma - Remote; Omaha, NE; Remote; St. Louis, MO; Wisconsin - Remote Company Description We are Olsson. We engineer and design solutions that improve the world around us. As a company, we promise to always be responsive, transparent, and focused on results – for our people, our clients, and our company. We’re a people-centric firm, so it’s no surprise our greatest asset is our people. The impact this creates is an environment that encourages our people to grow and be creative with their talents. This approach builds a culture that is uniquely Olsson. It allows us to grow our people as we grow our business. This, in turn, creates a lasting impact on the world around us. Job Description As a Lead Electrical Engineer, you will work directly with some of the world’s largest technology companies and other mission-critical clients.  You will serve as an electrical engineering lead on projects, design calculations, write technical reports, and prepare documents.  Experience in the Data Center industry is preferred. You will also coordinate with other Olsson teams, professional staff, technical staff, and clients. Qualifications You are passionate about: Working collaboratively with others. Having ownership in the work you do. Using your talents to positively affect communities. You bring to the team: Strong communication skills Ability to contribute and work well on a team Bachelor's degree in electrical engineering or related 13+ years of electrical engineering experience Licensed PE Experience with Revit CA experience Ability to be a self-starter to take on a variety of tasks to best serve the client and their project work Investigation and troubleshooting of problems to find solutions The typical annual salary range for this role is as listed below. Compensation may vary based on geographic location, experience, and qualifications. Employees in this role may be eligible for our performance‑based bonus and merit increases. National Pay Range $130,000 — $190,000 USD Additional Information Olsson specializes in engineering and design, client advisory services, planning, field services, and environmental. Improving the world has been our mindset from the very beginning, back when Olsson first opened for business in 1956. And it will be our mindset for years to come. As an Olsson employee, you will: Receive a competitive 401(k) match Be empowered to build your career with tailored development paths Have the possibility for flexible work arrangements Engage in work that has a positive impact on communities Participate in a wellness program promoting balanced lifestyles In addition, full-time employees will receive our traditional benefits package (health care, vision, dental, paid time off, etc.) and the opportunity to participate in a bonus system that rewards performance. Olsson is an Equal Opportunity Employer. We encourage qualified minority, female, veteran, and disabled candidates to apply and be considered for open positions. We do not discriminate against any applicant for employment or any employee because of race, color, religion, national origin, sex, sexual orientation, gender identity, gender, disability, age, military status, or other protected status. Olsson understands the importance of privacy and is committed to protecting job applicants’ personal information. Pursuant to the California Consumer Privacy Act, as amended by the California Privacy Rights Act (collectively, the “CCPA”), this notice explains Olsson’s practices regarding the collection, use, and disclosure of personal information for job applicants residing in California. Please read this Notice carefully to understand our privacy practices. For more information about the types of information we collect and how we use it in connection with your general access and use of our website, please review our general California Privacy Notice here .