scrumconnect ltd
Role Overview As Head of AI, you will be the primary technical driver of all AI/ML initiatives. You'll report directly to the CEO/CTO and own the full life cycle of our AI roadmap-from research and proof-of-concept to scalable production. We're looking for a doer who can rapidly prototype models, optimize for performance, and mentor junior engineers, all while helping define product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (eg, deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate AI features into our platform. Continuously evaluate new research, open-source tools, and emerging frameworks to keep us at the forefront. Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round. Key Responsibilities 1. Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (eg, neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure low-latency, high-availability inference. 2. Strategic Leadership Develop a multi-quarter AI roadmap aligned with product milestones and fundraising milestones. Identify and evaluate opportunities for AI-driven competitive advantages (eg, proprietary data, unique model architectures, transfer/few-shot learning). Collaborate with business stakeholders to translate big problems into technically feasible AI solutions. 3. Data & Infrastructure Oversee the creation and maintenance of scalable data pipelines (ETL/ELT) and data lakes/warehouses. Establish best practices for data labeling, versioning, and governance to ensure high data quality. Implement ML Ops processes: CI/CD for model training, automated testing, model-drift detection, and continuous monitoring. 4. Team Building & Mentorship Hire and mentor AI/ML engineers, data scientists, and research interns. Set coding standards, model-development guidelines, and rigor around reproducible experiments (eg, clear Git workflow, experiment tracking). Conduct regular code/model reviews and foster a culture of learn by doing and iterative improvement. 5. Research & Innovation Stay abreast of state-of-the-art AI research (eg, pre-training, fine-tuning, generative methods) and evaluate applicability. Publish or present whitepapers/prototype demos if appropriate (keeping stealth constraints in mind). Forge partnerships with academic labs or open-source communities to accelerate innovation. Minimum Qualifications Experience (7 + years total; 3 + years in senior/lead role): Demonstrated track record of shipping AI/ML products end-to-end (from prototype to production). Hands-on expertise building and deploying deep learning models (eg, CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). Leadership & Communication: Proven ability to lead cross-functional teams in ambiguous startup settings. Exceptional written and verbal communication skills-able to explain complex concepts to both technical and non-technical stakeholders. Experience recruiting and mentoring engineers or data scientists in a fast-paced environment. Education: Bachelor's or Master's in Computer Science, AI/ML, Electrical Engineering, Statistics, or a related field. (Ph.D. in AI/ML is a plus but not required if hands-on experience is extensive.) Preferred (Nice-to-Have) Prior experience in a stealth-mode or early-stage startup, ideally taking an AI product from 0 - 1. Background in a relevant domain (eg, healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). Hands-on experience with large-scale language models (LLMs) and prompt engineering (eg, GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (eg, TensorFlow Lite, ONNX, mobile/Embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.). Soft Skills & Cultural Fit Doer Mindset: You thrive in scrappy, ambiguous environments. You'll roll up your sleeves to write production code, prototype research ideas, and iterate quickly. Bias for Action: You favor shipping an MVP quickly, measuring impact, and iterating-over striving for perfect academic proofs that never see production. Ownership Mentality: You treat the startup as your own: you take responsibility for system uptime, data integrity, and feature adoption, not just model accuracy. Collaborative Attitude: You value cross-functional teamwork and can pivot between researcher mode and software engineer mode depending on the task at hand. Growth-Oriented: You continually learn new algorithms, architectures, and engineering best practices; you encourage team members to do the same. What We Offer Equity Package: Meaningful ownership stake, commensurate with an early leadership role. Competitive Compensation: Salary aligned with early-stage startup benchmarks; a large portion of the upside is in equity. Autonomy & Impact: You'll shape the technical direction of our AI stack and lay the groundwork for a market-leading product. Flexible Work Environment: Remote-friendly with occasional in-person retreats or team meetups. Learning Budget: Funds for conferences, courses, or publications to ensure you stay at the bleeding edge. Fast-Track Growth: As our first AI hire and eventual team leader, you'll rapidly expand your responsibilities-and the team you build-within months. How to Apply Please send your resume/CV and a brief cover letter with the subject line: Head of AI Application - [Your Name] In your cover letter, highlight: 1. A recent project where you built and deployed an AI/ML system end-to-end (include technical stack and impact). 2. Any leadership or mentoring experience guiding other engineers or data scientists. 3. Why you're excited to join a stealth startup and move quickly from prototype to production. We will review applications on a rolling basis and aim to schedule initial calls within two weeks of receipt. Equal Opportunity: We are committed to building a diverse team and welcome applicants of all backgrounds. We celebrate differences and encourage individuals who thrive in a fast-paced, collaborative, and impact-driven culture to apply. Ready to build world-class AI from day one? Come join us and help shape the future.
Role Overview As Head of AI, you will be the primary technical driver of all AI/ML initiatives. You'll report directly to the CEO/CTO and own the full life cycle of our AI roadmap-from research and proof-of-concept to scalable production. We're looking for a doer who can rapidly prototype models, optimize for performance, and mentor junior engineers, all while helping define product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (eg, deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate AI features into our platform. Continuously evaluate new research, open-source tools, and emerging frameworks to keep us at the forefront. Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round. Key Responsibilities 1. Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (eg, neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure low-latency, high-availability inference. 2. Strategic Leadership Develop a multi-quarter AI roadmap aligned with product milestones and fundraising milestones. Identify and evaluate opportunities for AI-driven competitive advantages (eg, proprietary data, unique model architectures, transfer/few-shot learning). Collaborate with business stakeholders to translate big problems into technically feasible AI solutions. 3. Data & Infrastructure Oversee the creation and maintenance of scalable data pipelines (ETL/ELT) and data lakes/warehouses. Establish best practices for data labeling, versioning, and governance to ensure high data quality. Implement ML Ops processes: CI/CD for model training, automated testing, model-drift detection, and continuous monitoring. 4. Team Building & Mentorship Hire and mentor AI/ML engineers, data scientists, and research interns. Set coding standards, model-development guidelines, and rigor around reproducible experiments (eg, clear Git workflow, experiment tracking). Conduct regular code/model reviews and foster a culture of learn by doing and iterative improvement. 5. Research & Innovation Stay abreast of state-of-the-art AI research (eg, pre-training, fine-tuning, generative methods) and evaluate applicability. Publish or present whitepapers/prototype demos if appropriate (keeping stealth constraints in mind). Forge partnerships with academic labs or open-source communities to accelerate innovation. Minimum Qualifications Experience (7 + years total; 3 + years in senior/lead role): Demonstrated track record of shipping AI/ML products end-to-end (from prototype to production). Hands-on expertise building and deploying deep learning models (eg, CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). Leadership & Communication: Proven ability to lead cross-functional teams in ambiguous startup settings. Exceptional written and verbal communication skills-able to explain complex concepts to both technical and non-technical stakeholders. Experience recruiting and mentoring engineers or data scientists in a fast-paced environment. Education: Bachelor's or Master's in Computer Science, AI/ML, Electrical Engineering, Statistics, or a related field. (Ph.D. in AI/ML is a plus but not required if hands-on experience is extensive.) Preferred (Nice-to-Have) Prior experience in a stealth-mode or early-stage startup, ideally taking an AI product from 0 - 1. Background in a relevant domain (eg, healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). Hands-on experience with large-scale language models (LLMs) and prompt engineering (eg, GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (eg, TensorFlow Lite, ONNX, mobile/Embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.). Soft Skills & Cultural Fit Doer Mindset: You thrive in scrappy, ambiguous environments. You'll roll up your sleeves to write production code, prototype research ideas, and iterate quickly. Bias for Action: You favor shipping an MVP quickly, measuring impact, and iterating-over striving for perfect academic proofs that never see production. Ownership Mentality: You treat the startup as your own: you take responsibility for system uptime, data integrity, and feature adoption, not just model accuracy. Collaborative Attitude: You value cross-functional teamwork and can pivot between researcher mode and software engineer mode depending on the task at hand. Growth-Oriented: You continually learn new algorithms, architectures, and engineering best practices; you encourage team members to do the same. What We Offer Equity Package: Meaningful ownership stake, commensurate with an early leadership role. Competitive Compensation: Salary aligned with early-stage startup benchmarks; a large portion of the upside is in equity. Autonomy & Impact: You'll shape the technical direction of our AI stack and lay the groundwork for a market-leading product. Flexible Work Environment: Remote-friendly with occasional in-person retreats or team meetups. Learning Budget: Funds for conferences, courses, or publications to ensure you stay at the bleeding edge. Fast-Track Growth: As our first AI hire and eventual team leader, you'll rapidly expand your responsibilities-and the team you build-within months. How to Apply Please send your resume/CV and a brief cover letter with the subject line: Head of AI Application - [Your Name] In your cover letter, highlight: 1. A recent project where you built and deployed an AI/ML system end-to-end (include technical stack and impact). 2. Any leadership or mentoring experience guiding other engineers or data scientists. 3. Why you're excited to join a stealth startup and move quickly from prototype to production. We will review applications on a rolling basis and aim to schedule initial calls within two weeks of receipt. Equal Opportunity: We are committed to building a diverse team and welcome applicants of all backgrounds. We celebrate differences and encourage individuals who thrive in a fast-paced, collaborative, and impact-driven culture to apply. Ready to build world-class AI from day one? Come join us and help shape the future.
ERSG
Sheffield, Yorkshire
BESS Design Engineer - Energy Storage Projects (Sheffield Based) A leading energy solutions provider is looking for a BESS Design Engineer to join its expanding team in Sheffield , supporting the design and development of Battery Energy Storage System (BESS) projects across the UK and internationally. This is a great opportunity to work on forward-thinking clean energy projects and contribute to the energy transition in a collaborative and supportive environment. You will be involved in the full technical life cycle of BESS installations, from early feasibility and concept development through to construction and commissioning support. Key Responsibilities: Design and review BESS systems, including single-line diagrams (SLDs), layout drawings, and equipment specifications Support feasibility studies and concept designs for grid-connected and hybrid energy projects Collaborate with control systems engineers to ensure well-integrated system solutions Prepare and review technical documentation, including employer's requirements and specifications Evaluate technology options including inverters, battery racks, HVAC systems, and fire protection equipment Assist in tender reviews and contractor design evaluations Support construction and commissioning with site visits, RFI responses, and review of as-built documentation The Ideal Candidate Will Have One or More of the Following: A degree, HND, or HNC in Electrical Engineering, Power Systems, Renewable Energy, or a related field Experience working on BESS or hybrid renewable projects such as solar plus storage A strong understanding of BESS technology or familiarity with key components like PCS, BMS, EMS, HVAC, or containerised systems Hands-on experience in electrical design or engineering, ideally with power systems or controls A passion for energy storage, clean energy, or power systems Proficiency in design tools such as AutoCAD, ETAP, or Trimble Awareness of UK grid codes or DNO connection standards is beneficial Excellent analytical, problem-solving, and communication skills Attention to detail and a desire to grow within a multi-disciplinary engineering team Location: Sheffield (flexible or hybrid working arrangements available) If you have experience or interest in electrical engineering and are eager to contribute to the future of energy storage, we welcome your application. ersg are an equal opportunities employer; we are committed to promoting equality of opportunity for all job applicants. We do not discriminate against applicants on the basis of age, sex, race, disability, pregnancy, marital status, sexual orientation, gender reassignment or religious background; all decisions are based on merit.
BESS Design Engineer - Energy Storage Projects (Sheffield Based) A leading energy solutions provider is looking for a BESS Design Engineer to join its expanding team in Sheffield , supporting the design and development of Battery Energy Storage System (BESS) projects across the UK and internationally. This is a great opportunity to work on forward-thinking clean energy projects and contribute to the energy transition in a collaborative and supportive environment. You will be involved in the full technical life cycle of BESS installations, from early feasibility and concept development through to construction and commissioning support. Key Responsibilities: Design and review BESS systems, including single-line diagrams (SLDs), layout drawings, and equipment specifications Support feasibility studies and concept designs for grid-connected and hybrid energy projects Collaborate with control systems engineers to ensure well-integrated system solutions Prepare and review technical documentation, including employer's requirements and specifications Evaluate technology options including inverters, battery racks, HVAC systems, and fire protection equipment Assist in tender reviews and contractor design evaluations Support construction and commissioning with site visits, RFI responses, and review of as-built documentation The Ideal Candidate Will Have One or More of the Following: A degree, HND, or HNC in Electrical Engineering, Power Systems, Renewable Energy, or a related field Experience working on BESS or hybrid renewable projects such as solar plus storage A strong understanding of BESS technology or familiarity with key components like PCS, BMS, EMS, HVAC, or containerised systems Hands-on experience in electrical design or engineering, ideally with power systems or controls A passion for energy storage, clean energy, or power systems Proficiency in design tools such as AutoCAD, ETAP, or Trimble Awareness of UK grid codes or DNO connection standards is beneficial Excellent analytical, problem-solving, and communication skills Attention to detail and a desire to grow within a multi-disciplinary engineering team Location: Sheffield (flexible or hybrid working arrangements available) If you have experience or interest in electrical engineering and are eager to contribute to the future of energy storage, we welcome your application. ersg are an equal opportunities employer; we are committed to promoting equality of opportunity for all job applicants. We do not discriminate against applicants on the basis of age, sex, race, disability, pregnancy, marital status, sexual orientation, gender reassignment or religious background; all decisions are based on merit.
