ml engineer

Ventula Consulting

<div>
 
 
 AI / ML Engineer - AI Startup - London - &pound;80k - &pound;120k
 
 
 
 
 
 
 A newly established Voice AI startup with multi-million funding, is looking to hire an AI / ML Engineer to focus on their ML pipelines which process very high-volume events at scale.
 
 
 
 
 
 Our client is looking for an individual with significant experience as either an AI Engineer or Machine Learning Engineer with clear evidence of shipping LLM powered ML products
 
 
 
 
 
 To be suitable for this role you will require the below:
 
 
 
 
 
 
 Key Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Machine Learning, or a related field
 </li>
 <li>
 Excellent experience as a, ML, or AI Engineer, with evidence of shipping production systems
 </li>
 <li>
 Strong Python skills and experience with FastAPI
 </li>
 <li>
 Experience working modern MLOps tools, ideally Kubeflow
 </li>
 <li>
 Strong experience working closely with LLMs (including fine-tuning, RAG, prompt engineering)
 </li>
 <li>
 Strong problem-solving skills and ability to communicate technical trade-offs clearly
 </li>
 <li>
 Collaborative mindset with experience working across technical and non-technical teams
 </li>
 </ul>
 
 
 
 
 
 
 
 This position is a permanent role, based in London, with 3-4 days a week in the company's office
 
 
 
 
 
 The role offers a salary between &pound;80,000 - &pound;120,000
 
</div>

AI / ML Engineer

Natural Negative

<div>About Natural Negative
Natural Negative is a materials science company optimising biomaterials science with AI. We design compostable formulations that match or surpass conventional plastics: production-ready and drop-in compatible with existing manufacturing lines.
We believe everything humans encounter and consume should make them healthier. The biomaterials that could deliver that already exist; the industry hasn't yet made them practical to adopt at scale. We're optimising that: faster, cheaper, less risky.
We're investor-backed, with active Innovate UK grants and partnerships across leading research and innovation organisations. Our lab is at Plus X Innovation Hub, Brighton.
The role
As our ML engineer, you'd own our cloud ML infrastructure, building it out closely with the CTO, who leads the technical direction. You'd work alongside our full-stack engineer to get ML capabilities into the product, and with the materials scientists running the experiments your models train on.
In practice:<ul><li>
Stand up and run our production ML stack on GCP.</li><li>
Design and automate the pipelines that move experimental data out of the lab and into training.</li><li>
Bring real engineering discipline to the models: CI/CD, testing, dataset and checkpoint versioning.</li><li>
Help shape how it all fits together, alongside the CTO.</li><li>
Contribute to the next generation of our modelling with the founding team.</li></ul>
You'd be early enough to shape how we build, and the systems you stand up will support the platform as it grows. And you'd be working with materials science data, closer to the underlying science than most ML roles ever get.
How we work
We say what we think, kindly. We move thoughtfully. Sprint culture doesn't solve materials science problems. We're here because the problem is interesting and the science is unfinished. 
Requirements 
Must have:<ul><li>
Production ML experience: you've built and run ML systems before and can own your delivery, with the CTO setting the wider technical direction.</li><li>
Strong Python and production ML experience (PyTorch or similar), with hands-on containerised deployment to GCP or comparable platforms.</li><li>
A track record of building and running ML/data pipelines in small teams, comfortable when not much infrastructure is handed to you.</li><li>
A systems mindset: you decouple cleanly, think in modules, and can hold the shape of a whole pipeline in your head.</li><li>
Genuine interest in the underlying problem. You'd be working with materials data; if that doesn't sound interesting, this isn't the role.</li></ul>
Nice to have:<ul><li>
Experience applying ML in scientific, materials, or engineering domains.</li></ul>
How you work:<ul><li>
You take ownership and finish what you start.</li><li>
You have opinions and you say them, but they're rooted in considered thinking rather than reflex.</li><li>
You're a good colleague: friendly, empathetic, and able to operate in a flat team.</li></ul> 

Benefits 
<ul><li>
A competitive salary + meaningful equity.</li><li>
A direct working relationship with the founders. No layers between you and the people making decisions.</li><li>
28 days holiday plus bank holidays.</li><li>
Workplace pension scheme.</li><li>
Remote working, with lab and studio space at Plus X Innovation Hub, Brighton, if you want it.</li><li>
A team that doesn't reward presenteeism and doesn't micromanage. Family, rest, and time to think are how good work gets done, not what gets traded to do it.</li></ul></div>

MLOps/ ML Engineer

malomatia

<div>
 
 Job Description
 
 
 
 Must Have
 
 
 <ul>
 <li>
 4+ years of software or machine-learning engineering experience, including hands-on experience deploying models to production.
 </li>
 <li>
 Demonstrated track record operationalizing models developed by data scientists into reliable, scalable, and observable production systems.
 </li>
 <li>
 Production experience with classical machine-learning workloads &mdash; distinct from generative-AI application development.
 </li>
 <li>
 Strong collaboration skills across data science, software engineering, and platform teams.
 </li>
 <li>
 Commitment to building reliable, well-engineered, and maintainable systems.
 
 
 </li>
 </ul>
 Nice to Have
 
 
 <ul>
 <li>
 Experience with feature stores and large-scale or streaming data pipelines.
 </li>
 <li>
 Knowledge of infrastructure-as-code (e.g., Terraform) and cloud cost optimization.
 </li>
 <li>
 Experience with workflow orchestration tools (e.g., Apache Airflow).
 </li>
 <li>
 Familiarity with model-serving frameworks and API design for inference.
 </li>
 <li>
 Light exposure to generative-AI or LLM deployment.
 </li>
 <li>
 Experience operating systems in a regulated or enterprise environment.
 </li>
 <li>
 Cloud or MLOps certifications.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Build, deploy, and maintain production machine-learning pipelines, from data ingestion and feature processing through to model serving.
 </li>
 <li>
 Operationalize models developed by data scientists, ensuring reliability, scalability, reproducibility, and performance.
 </li>
 <li>
 Implement MLOps practices including CI/CD for machine learning, model versioning, automated retraining, and model registries.
 </li>
 <li>
 Design and maintain feature pipelines and, where relevant, feature stores.
 </li>
 <li>
 Set up monitoring and alerting for model performance, data drift, and system health, and respond to degradation.
 </li>
 <li>
 Optimize inference latency, throughput, and resource cost for deployed models.
 </li>
 <li>
 Containerize and orchestrate machine-learning workloads using Docker and Kubernetes on Oracle Cloud Infrastructure (OCI).
 </li>
 <li>
 Automate and harden data and model workflows to reduce manual intervention.
 </li>
 <li>
 Collaborate with data scientists on model handoff, packaging, and success metrics.
 </li>
 <li>
 Work with software engineers to integrate models into client-facing applications and services.
 </li>
 <li>
 Apply software-engineering best practices including testing, code review, and documentation to machine-learning systems.
 </li>
 <li>
 Troubleshoot and resolve production issues across the model-serving stack.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, or a related field; equivalent experience accepted.
 </li>
 <li>
 Strong Python engineering skills and production experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
 </li>
 <li>
 Hands-on experience with MLOps tooling (e.g., MLflow, Kubeflow) and CI/CD pipelines.
 </li>
 <li>
 Proficiency with containerization and orchestration (Docker, Kubernetes).
 </li>
 <li>
 Experience building and maintaining data pipelines and processing large datasets.
 </li>
 <li>
 Experience with cloud infrastructure, ideally Oracle Cloud Infrastructure (OCI) and OCI Data Science.
 </li>
 <li>
 Understanding of model monitoring, drift detection, and retraining strategies.
 </li>
 <li>
 Solid software-engineering fundamentals including testing and version control.
 </li>
 </ul>
</div>

ML Engineer

<div>Role description 
AI/ML Engineer

ML Engineer I 


Who We Are:

Born digital, UST transforms lives through the power of technology. We walk alongside our clients and partners, embedding innovation and agility into everything they do. We help them create transformative experiences and human-centered solutions for a better world.

UST is a mission-driven group of 29,000+ practical problem solvers and creative thinkers in more than 30 countries. Our entrepreneurial teams are empowered to innovate, act nimbly, and create a lasting and sustainable impact for our clients, their customers, and the communities in which we live.

With us, you&rsquo;ll create a boundless impact that transforms your career&mdash;and the lives of people across the world.

Visit us at UST.com. 


You Are:

UST is searching for an AI/ML Engineer, you must have 3-5 years MLOps with AWS + Databricks + Snowflake. 


The opportunity:
<ul><li> Build MCP Servers for CIE (expose scoring, rules, explainability as MCP tools via Model Context Protocol)</li></ul>
<ul><li> Integrate with AgentCore Gateway (JWT/mTLS authentication, entitlement checks, routing)</li></ul>
<ul><li> AWS Bedrock integration for LLM explainability via AI Marketplace subscription</li></ul>
<ul><li> PHI guardrails implementation (pre-request scanning, post-response masking for healthcare data)</li></ul>
<ul><li> MLflow model registry (versioning, A/B testing, rollback), Build CI/CD for model deployment</li></ul>
<ul><li> Feature store integration (Databricks Feature Store MCP tools)</li></ul>
<ul><li> OpenTelemetry instrumentation (usage events emission to AI Marketplace metering)</li></ul>
<ul><li> MCP tool manifest registration (score_claim, explain_detection, provider_profile tools)</li></ul> 


This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required. 
What you need:
<ul><li> AWS/ Databricks Certified (preferred) Python 5+ years</li></ul>
<ul><li> Familiarity with MCP Protocol (Model Context Protocol) - build MCP servers that expose tools</li></ul>
<ul><li> MLOps/MLflow 3+ years (model registry, serving) on AWS and Databricks</li></ul>
<ul><li> Databricks Model Serving production (REST API endpoints)</li></ul>
<ul><li> Snowflake UDF + external function deployment</li></ul>
<ul><li> OAuth2/JWT authentication + mTLS certificate handling</li></ul>
<ul><li> AWS Bedrock (LLM integration for explainability)</li></ul>
<ul><li> AgentCore Gateway integration (JWT validation, entitlement enforcement, tool routing)</li></ul>
<ul><li> PHI/HIPAA compliance (pre/post-request PHI scanning)</li></ul>
<ul><li> OpenTelemetry (usage event emission, distributed tracing)</li></ul>
<ul><li> REST API development (MCP tool endpoints)</li></ul>
<ul><li> Docker/containerization</li></ul>
<ul><li> Monitoring (Databricks, CloudWatch), Git + GitHub + CI/CD</li></ul>
<ul><li> Must understand MCP Protocol or willingness to learn (AWS AgentCore documentation)</li></ul>
<ul><li> Must have worked with OAuth2-secured APIs</li></ul> 


Compensation can differ depending on factors including but not limited to the specific office location, role, skill set, education, and level of experience. UST provides a reasonable range of compensation for roles that may be hired in various U.S. markets as set forth below.

Role Location: Illinois

Compensation Range: $72,000-$108,000 


Benefits

Full-time, regular employees accrue a minimum of 10 days of paid vacation per year, receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year), 10 paid holidays, and are eligible for paid bereavement leave and jury duty. They are eligible to participate in the Company&rsquo;s 401(k) Retirement Plan with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance, as well as the following Company-paid Employee Only benefits: basic life insurance, accidental death and disability insurance, and short- and long-term disability benefits. Regular employees may purchase additional voluntary short-term disability benefits, and participate in a Health Savings Account (HSA) as well as a Flexible Spending Account (FSA) for healthcare, dependent child care, and/or commuting expenses as allowable under IRS guidelines. Benefits offerings vary in Puerto Rico.

Part-time employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company&rsquo;s 401(k) Retirement Plan with employer matching.

Full-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company&rsquo;s 401(k) program with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance.

Part-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year).

All US employees who work in a state or locality with more generous paid sick leave benefits than specified here will receive the benefit of those sick leave laws. 


What we believe:

We proudly embrace the values that have shaped UST since day one. We build our culture of Humility, Humanity, and Integrity. These values inspire us to nurture a people-first, human centric culture that fosters diversity, prioritizes sustainable solutions, and keeps our people and clients at the forefront of all decisions. 


Humility:

We will listen, learn, be empathetic and help selflessly in our interactions with everyone.

Humanity:

Through business, we will better the lives of those less fortunate than ourselves.

Integrity:

We honor our commitments and act with responsibility in all our relationships. 


Equal Employment Opportunity Statement 
UST is an Equal Opportunity Employer. 


All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other applicable characteristics protected by law. We will consider qualified applicants with arrest or conviction records in accordance with state and local laws and &ldquo;fair chance&rdquo; ordinances.

UST reserves the right to periodically redefine your roles and responsibilities based on the requirements of the organization and/or your performance. 


#UST

#CB

#LI-AP6 
Skills 
aws,hipaa compliance,aws databricks,json web token,rest api development,cicd,docker containerization, 
Benefits 
Compensation range: $72,000.00 to $108,000.00 per year 
About UST 
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world&rsquo;s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients&rsquo; organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact&mdash;touching billions of lives in the process.</div>

AI/ML Engineer 

Accenture in India

<div>
 
 Project Role :
 
 AI / ML Engineer
 
 
 
 Project Role Description :
 
 Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
 
 
 
 Must have skills :
 
 Machine Learning (ML)
 
 
 
 Good to have skills :
 
 NA
 
 
 
 Minimum 3 Year(s) Of Experience Is Required
 
 
 
 
 Educational Qualification :
 
 15 years full time education
 
 
 Role Summary
 
 
 We are seeking a hands-on AI Native Engineer who can design, build, and deploy end-to-end agentic and LLM-powered systems. This includes constructing RAG pipelines, working with vector databases, building autonomous or semi-autonomous agents, integrating tools and skills, and developing evaluation frameworks for high-quality AI behaviour. You will prototype rapidly, experiment with models, and evolve solutions from PoC to production while working closely with cross-functional teams.
 
 
 AI Powered Tech Talent
 
 
 Key Responsibilities
 
 
 Agentic &amp; LLM System Development
 
 
 Build agentic AI systems, including agent orchestration, planning loops, tool calling, and memory modules.
 
 
 Implement LLM toolchains, custom prompts, templates, evaluators, and multi-step reasoning workflows.
 
 
 Develop autonomous/semi-autonomous agents for retrieval, summarization, decision support, or workflow automation.
 
 
 RAG Pipelines &amp; Vector Intelligence
 
 
 Design and implement RAG pipelines end-to-end: ingestion, chunking, embeddings, indexing, vector search, hybrid retrieval, and grounding.
 
 
 Integrate vector databases such as pgvector, Pinecone, Weaviate, or Milvus.
 
 
 Optimize retrieval quality, latency, and factual accuracy using rerankers, retrieval evaluators, and freshness pipelines.
 
 
 Model Integration &amp; AI Ops
 
 
 Integrate enterprise-grade AI APIs, foundation models, and transformer models into scalable systems.
 
 
 Implement robust evaluation frameworks including offline and online evals, regression tests, content safety checks, and red-team scenarios.
 
 
 Build monitoring for model drift, agent failure modes, hallucination detection, and end-to-end system health.
 
 
 Full-Stack &amp; Cloud Alignment
 
 
 Deploy services using Python/Node/Java microservices, serverless functions, or containerized workloads.
 
 
 Integrate event streams, API gateways, and cloud-native patterns across Azure/AWS/GCP.
 
 
 Build CI/CD pipelines for AI services with safe rollouts, versioning, and feature flags for model updates.
 
 
 Prototyping &amp; Rapid Iteration
 
 
 Rapidly experiment with models, embeddings, architectures, and agentic patterns.
 
 
 Translate business requirements into AI-native technical architectures and communicate trade-offs via demos and deep-dives.
 
 
 Document designs, experiments, and evaluation results for reproducibility and knowledge sharing.
 
 
 Professional &amp; Technical Skills
 
 
 Must-Have (AI Native Core)
 
 
 Hands-on experience with LLMs, agent frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, AutoGen), and vector DBs.
 
 
 Strong Python skills for building agents, RAG services, data pipelines, and evaluation harnesses.
 
 
 Deep understanding of transformer models, embeddings, prompt engineering, and model fine-tuning workflows.
 
 
 Experience deploying AI systems to production with monitoring, error handling, retries, and fallback strategies.
 
 
 Good to Have
 
 
 Experience with cloud AI platforms (Azure OpenAI, Bedrock, Vertex AI).
 
 
 Knowledge of multimodal models, reinforcement learning, or advanced reasoning agents.
 
 
 Familiarity with evaluation frameworks (pytest, JUnit) and custom eval harnesses.
 
 
 Additional Information
 
 
 Minimum 3 years of experience in ML/AI engineering (AI-native experience preferred).
 
 
 Location: Bengaluru.
 
 
 Education: 15 years full-time education., 15 years full time education
</div>

<div>
 
 Project Role :
 
 AI / ML Engineer
 
 
 
 Project Role Description :
 
 Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
 
 
 
 Must have skills :
 
 Large Language Models (LLMs), SAP CRM interaction Center
 
 
 
 Good to have skills :
 
 NA
 
 
 
 Minimum 3 Year(s) Of Experience Is Required
 
 
 
 
 Educational Qualification :
 
 15 years full time education
 
 
 Summary:
 
 
 As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence technologies. This role requires integrating cloud-based or on-premises pipelines to ensure solutions are production-ready and scalable. The work often includes applying generative artificial intelligence models and exploring various domains such as deep learning, neural networks, conversational agents, and image analysis. Collaboration with cross-functional teams to align technical implementations with project goals is a key aspect of daily activities, fostering innovation and continuous improvement in AI-driven solutions.
 
 
 Roles &amp; Responsibilities:
 
 
 <ul>
 <li>
 Expected to perform independently and become an SME.
 </li>
 <li>
 Required active participation/contribution in team discussions.
 </li>
 <li>
 Contribute in providing solutions to work related problems.
 </li>
 <li>
 Collaborate with team members to refine and optimize AI models and system architectures.
 </li>
 <li>
 Assist in documenting technical processes and best practices to support knowledge sharing.
 </li>
 <li>
 Support junior team members by providing guidance and sharing expertise to foster their professional growth.
 
 
 
 </li>
 </ul>
 Professional &amp; Technical Skills:
 
 
 <ul>
 <li>
 Must To Have Skills: Proficiency in Large Language Models (LLMs).
 </li>
 <li>
 Experience with designing and deploying AI applications using cloud AI services and on-premises infrastructure.
 </li>
 <li>
 Strong understanding of generative artificial intelligence models and their practical applications.
 </li>
 <li>
 Familiarity with deep learning frameworks and neural network architectures.
 </li>
 <li>
 Ability to develop and maintain production-quality AI pipelines ensuring robustness and scalability.
 </li>
 <li>
 Knowledge of chatbot development and image processing techniques.
 
 
 
 </li>
 </ul>
 Additional Information:
 
 
 <ul>
 <li>
 The candidate should have minimum 3 years of experience in Large Language Models (LLMs).
 </li>
 <li>
 This position is based at our Indore office.
 </li>
 <li>
 A 15 years full time education is required.
 
 
 
 </li>
 </ul>
 , 15 years full time education
</div>

Egen Solutions Inc

<div><div><div><div>Job Description :</div>
<div></div>
<div>We are seeking a highly motivated and experienced Lead ML Engineer to join our growing ML/GenAI team.</div>
<div></div>
<div>You will play a key role in designing, developing and productionalizing ML/GenAI applications by evaluating models, training and/or fine tuning them. As a lead, you require a deep understanding of both machine learning algorithms and software architecture. You need to take ownership of projects from conception to deployment, collaborating with engineers and stakeholders to ensure successful project delivery.</div>
</div></div><div><div><h3 class="jobSectionHeader">What we're looking for:</h3><div><div><div>
<ul><li>At least 5 years of experience in designing &amp; building ML/AI applications for customer and deploying them into production</li>
<li>At least 8 years of Software engineering experience in building Secure, scalable and performant applications for customers.</li>
<li>At least 2 years of experience leading and mentoring ML/data science teams( 4+ team members)</li>
<li>Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI.</li>
<li>Design, develop, and operationalize existing ML models by fine tuning, personalizing it.</li>
<li>Evaluate machine learning models and perform necessary tuning.</li>
<li>Develop prompts that instruct LLM to generate relevant and accurate responses.</li>
<li>Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.</li>
<li>Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.</li>
<li>Lead the end-to-end design and architecture of scalable, reliable, and cost-effective Generative AI solutions. This includes designing RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and model fine-tuning strategies.</li>
<li>Hands on customer experience with RAG solution or fine tuning of LLM model.</li>
<li>Build and deploy scalable machine learning pipelines on Google Cloud or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.</li>
<li>Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment.</li>
<li>Act as the senior-most developer, writing clean, high-quality, and scalable code. This includes building core components for prompt engineering, vector search, data processing, model evaluation, and inference serving.</li>
<li>Proven experience building and deploying machine learning models in production environments for real life applications</li>
<li>Good understanding of natural language processing, computer vision or other deep learning techniques.</li>
<li>Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).</li>
<li>Familiarity with Google Cloud or any other Cloud Platform</li>
</ul></div></div></div></div></div><div><div><h3 class="jobSectionHeader">Good to Have
</h3><div><div><div><ul><li>Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.</li>
<li>Experience of working with one or more public cloud platforms - namely Google Cloud, AWS or Azure.</li>
<li>Experience with AutoML and vision techniques.</li>
<li>Master&rsquo;s degree in statistics, machine learning or related fields.</li>
</ul></div></div></div></div></div><div><div>We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</div></div></div>

Lead-ML Engineer

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