Ai Algorithms Specialist Jobs

At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities: Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast. Required Skills: 3+ years of hands-on ML experience with deep practical real-world experience in training models. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization

About AiDASH AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com. The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024. Join us in Securing Tomorrow Together! The Role As a Geospatial Analyst at AiDASH, you will produce high-quality annotated datasets from diverse imagery sources — satellite, LiDAR, aerial, and ground-based panoramic images and videos. Your work will directly feed AI/ML pipelines and client deliverables that protect critical infrastructure. This role demands a sharp eye for detail, comfort working with visual and geospatial data at scale, and fluency with modern AI tools. You won’t just annotate images; you’ll build AI-accelerated workflows that make the entire team faster. How You’ll Make an Impact Annotate and label imagery (satellite, LiDAR, aerial, drone, ground-based panoramic photos and videos) to identify, classify, and delineate features such as vegetation, assets, terrain, and infrastructure components Prepare,

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a skilled Software Engineer with a passion for building high-performance, low-level systems software. In this role, you’ll contribute to the development and optimization of the infrastructure that powers our cutting-edge processors, with a primary focus on C/C++ development and low-level programming. You'll work closely with large inference and training model development to further drive Scale Out software and hardware performance. This role is hybrid, based out of Toronto, ON. Who You Are Strong C or C++ systems engineer with a deep understanding of memory, threading, I/O, and low-level execution models. Experienced building low-level software, drivers, embedded systems, or performance-critical infrastructure. Comfortable working close to hardware and curious about how systems behave under the hood. Proficient with Linux systems programming and debugging tools such as gdb, strace, and perf. Structured problem solver who thrives in fast-paced, highly technical environments. What We Need Design, develop, and maintain core infrastructure software that interfaces directly with Tenstorrent hardware. Build low-level libraries and APIs for communication and synchronization across compute nodes. Optimize system-level software for performance, scalability, and reliability in distributed environments. Support hardware

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building the world’s fastest, most efficient AI compute clusters. TT-Fabric is the high-performance nervous system of this platform: the low-level networking layer that lets thousands of RISC-V and AI processors snap together into a single, massively parallel distributed supercomputer. If you love squeezing nanoseconds out of hot paths, designing protocols that move data at absurd scale, and turning messy hardware constraints into elegant distributed systems, this is an opportunity to shape the fabric that future AI models will run on This role is hybrid based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who We Are Strong systems engineer with deep C or C++ experience and comfort working in low-level or bare-metal environments. Passionate about hardware-software interaction, performance tuning, and eliminating inefficiencies at the protocol level. Curious about networking, synchronization, and communication across large clusters. Comfortable reasoning from first principles and challenging industry conventions. Motivated by building infrastructure that directly impacts large-scale

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. At Tenstorrent, we are building open, scalable compute for real AI workloads. As Director, Customer Hardware Engineering, you own the technical relationship with strategic customers and FAEs, turning their silicon needs into precise requirements for our hardware and software teams. You connect customer architectures to Tenstorrent platforms so their models run efficiently on our silicon. This role is hybrid, based out of Toronto, Austin, TX or Belgrade, Serbia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced leader of customer-facing technical teams and Field Application Engineering organizations. Strong background across RTL, verification, and physical design for custom silicon programs. Systems thinker who understands how RTL choices affect software, performance, and customer solutions. Clear communicator who aligns customers, FAEs, and internal teams around shared technical goals. What We Need Own technical customer relationships and convert high-level asks into concrete engineering specifications. Coordinate with hardware and software leads on customer-specific NEO silicon configurations. Oversee RTL changes and NEO cus

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Our Tensix Team is building the next generation of high-performance AI compute systems. We’re looking for a Power Architect to drive architectural strategy, modeling, and design decisions that shape how power is understood and optimized across our products. This is a hands-on role with massive influence over how we build power-aware systems from the ground up. This role is hybrid, based out of Santa Clara, CA, Boston, MA, Austin, TX or Toronto. We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are 15+ years experience with power estimation tools like PowerArtist, PtPX, RTL Architect, and PrimePower. Skilled in modeling and optimizing power at the architectural level, with deep knowledge of power-gating, voltage domains, and leakage control. Track record of influencing architectural and micro-architectural changes that meaningfully reduced design power. Proficient in Verilog HDL, Design Compiler, C/C++ and Python. Background in power-optimization of compute datapath and/or interconnects. What We Need Predict power consumption early in architecture and track it through RTL evolution. Propose architectural changes for power optimization across server and non-

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building next-generation CPU and AI silicon. You’ll work at the forefront of hardware innovation, diagnosing complex issues across chips, systems, firmware, and software while collaborating with some of the brightest engineers in the industry. This role offers the opportunity to solve challenging technical problems, build impactful debug solutions, and directly influence the reliability and performance of cutting-edge AI compute platforms. This role is hybrid, based out of Toronto, Canada. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced in hardware debug and post-silicon bring-up for CPU, SoC, or ASIC systems. Strong understanding of processor architecture and microarchitecture (RISC-V, x86, or ARM) with familiarity in debug and trace methodologies (e.g., iJTAG). Hands-on engineer who excels at diagnosing complex hardware, firmware, and software issues through root-cause analysis. Comfortable working in the lab with a passion for building debug tools, automation, and scalable methodologies. Collaborative team player with experience partnering across ASIC, firmware, software, and validation teams. What We Need

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As Engineering Manager for the Agent Execution group , you'll lead more than 10 engineers who build foundations for AI agents to run safely and effectively across GitLab. You'll give the group clarity, remove obstacles, and help teams move quickly while protecting what matters. You'll contribute to design reviews on sandboxing and agent observability, work alongside staff engineers, and use modern AI coding tools and agent harnesses in your work. What you’ll do Lead the Agent Tools, Agent Observability, and Runner Execution teams across frontend, backend, and AI engineering, with each team anchored by a s

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on the Flow Components functional team , you'll help build GitLab's Flow Registry, which provides reusable primitives for agentic flows built on the GitLab Duo Agent Platform. Your primary focus will be backend engineering in Python, using LangChain and LangGraph to develop secure, reliable, and scalable capabilities across the Duo Workflow Service and the GitLab monolith. You'll also work across the stack when needed, bringing familiarity with JavaScript and frontend development to support the official GitLab Duo Agent Platform client, Duo CLI, and advocate for a strong user

AI agents are transforming the way developers interact with software - and databases are no exception. We're seeking a Software Engineer to join our AI Interfaces team within AI Builder Experience (ABX), where you'll provide technical direction, shape architecture, and build the core products that make it seamless for developers and AI agents to work with MongoDB. Our team owns the surfaces through which humans and agents connect to MongoDB - including the MongoDB MCP Server, Agent Skills, our Intelligent Assistant Platform, and purpose-built agents. In short: if it's how an agent talks to MongoDB, we're building it. This is a new team charting new territory, and as a Software Engineer here, you'll be right at the frontier - building the technologies that let AI applications and agentic workflows work seamlessly with MongoDB at scale. You'll integrate with fast-moving, often unproven technologies, make pragmatic calls in the face of ambiguity, and own high-visibility projects end to end with minimal guidance. We're looking for product-minded engineers who thrive on autonomy and take pride in shipping. MongoDB engineering teams pride themselves on building high-quality software and living our cultural values every day - we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. This position requires participation in a 24/7 on-call rotation to ensure business continuity and incident response capabilities. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Work closely with research, product management, product engineering, product design, peers, as well as other teams within the company to define the first version and future evolution of our AI interfaces Design, build, and deliver well-tested core pieces of the platform - including the MongoDB MCP Server, Agent Skills, the Intelligent Assistant Platform, and purpose-built

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