Deepak Mishra - Lead ML Platform Engineer

Q: Where is Deepak based?

Deepak is based in Berlin, Germany .

Q: What languages does Deepak speak?

Deepak speaks the following languages: English (Advanced), German (Intermediate) .

Q: How many years of experience does Deepak have?

Deepak has at least 9 years of experience. During this time, Deepak has worked in at least 4 different roles and for 5 different companies . The average length of individual experience is 2 years and 10 months . Note that Deepak may not have shared all experience and actually has more experience.

Q: What is Deepak's latest experience?

Deepak's most recent position is Lead ML Platform Engineer at Billie GmbH .

Q: What companies has Deepak worked for in recent years?

In recent years, Deepak has worked for Billie GmbH , TwoTronic GmbH , Latana GmbH , and Candis GmbH .

Q: Which industries is Deepak most experienced in?

Deepak is most experienced in industries like Banking and Finance , Information Technology , and Fashion . Deepak also has some experience in Retail and Automotive .

Q: Which business areas is Deepak most experienced in?

Deepak is most experienced in business areas like Information Technology , Product Development , and Business Intelligence . Deepak also has some experience in Project Management .

Q: Which industries has Deepak worked in recently?

Deepak has recently worked in industries like Banking and Finance , Information Technology , and Automotive .

Q: Which business areas has Deepak worked in recently?

Deepak has recently worked in business areas like Information Technology , Product Development , and Business Intelligence .

Recommended expert

Berlin, Germany

Check rate

Experience

Jan 2025 - Dec 2025

1 year

Berlin, Germany

Lead ML Platform Engineer

Billie GmbH

Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices

Dec 2023 - Nov 2024

1 year

Berlin, Germany

Lead Machine Learning Engineer

TwoTronic GmbH

Mentor squad of 3 ML engineers on computer vision model development, deployment practices, and production best practices; conduct code reviews and technical design sessions
Architect and deliver production-ready computer vision pipelines for vehicle damage detection and information extraction, processing 100K+ images daily with 95% accuracy; own full ML lifecycle from data annotation to production monitoring
Build multi-tenant and single-tenant architecture supporting 5+ enterprise clients with isolated model inference pipelines on Kubernetes; implement autoscaling reducing infrastructure costs by 30%
Establish automated ML pipelines for model retraining, A/B testing, and gradual rollouts; reduce model update cycle from 4 weeks to 1 week through full automation

Aug 2021 - Nov 2023

2 years 4 months

Berlin, Germany

Senior Machine Learning Engineer

Latana GmbH

Design and deploy automated ML pipelines using Metaflow for distributed training and batch inference at scale, processing 10M+ survey responses monthly with reproducible, versioned workflows
Establish Agile/Scrum processes for a 12-person Data Science team, facilitate sprint planning and retrospectives, and collaborate with DevOps on deployment automation, reducing release cycles by 40%
Integrate monitoring, logging, and debugging tools directly in production code, reducing mean time to resolution by 55% and improving model reliability to 99.2% uptime
Partner with Data Engineering, DevOps, and Product teams to align ML model requirements with business metrics and infrastructure capabilities

Dec 2017 - Jul 2021

3 years 8 months

Berlin, Germany

Hybrid

Senior Machine Learning Engineer

Candis GmbH

Architect scalable ML infrastructure supporting 8+ production models with hybrid cloud deployment (AWS and on-premise Kubernetes); establish model versioning, A/B testing framework, and deployment standards
Mentor and upskill 4 junior ML engineers on production ML best practices, code quality, and system design; achieve 2 promotions to mid-level roles within 18 months
Deliver Invoice Classification & Extraction (93% F1 score), Transaction Fee Parsing, Fraud Detection (reduce fraud by 40%), Customer Metrics Tracking, and NLP pipelines using deep neural networks, graph algorithms, and embeddings
Implement end-to-end deployment pipelines on AWS (SageMaker, Lambda, Elastic Beanstalk) and on-premise Kubernetes using Helm Charts, Spinnaker, and Terraform; establish CI/CD, monitoring, and observability best practices
Leverage graph-based algorithms for transaction relationship modeling, embedding techniques for semantic document search, and distributed training for large-scale neural networks

Sep 2016 - Nov 2017

1 year 3 months

Berlin, Germany

Machine Learning Engineer

Lesara GmbH

Serve as sole ML engineer delivering end-to-end ML solutions within Agile sprints, including recommendation engines (20% CTR improvement), CLV estimation, real-time gender prediction using Bayesian models, and Google Ads bidding optimization (15% ROAS improvement)

Industry Experience

See where this freelancer has spent most of their professional time.

Experienced in Banking and Finance, Information Technology, Automotive, Fashion, and Retail.

Banking and Finance

Information Technology

Automotive

Fashion

Retail

Business Area Experience

See which departments and functions this freelancer has contributed to most.

Experienced in Information Technology, Product Development, Business Intelligence, and Project Management.

Information Technology

Product Development

Business Intelligence

Project Management

Summary

Lead ML Platform Engineer with 8+ years architecting scalable ML infrastructure, leading engineering squads, and delivering production-ready AI/ML solutions. Proven expertise in building end-to-end MLOps platforms, mentoring engineering teams of 5-8 members, and defining technical strategy for ML systems serving millions of users. Deep experience with cloud platforms (AWS/GCP-ready), Kubernetes orchestration, ML workflow automation (Airflow, Metaflow, Vertex Pipelines-compatible), and modern AI technologies (LLMs, RAG systems, Vector DBs). Track record of reducing deployment cycles by 40%, improving model reliability to 99.5% uptime, and driving $200K+ annual cost optimizations through infrastructure automation.

Skills

Ml Platform Architecture
Distributed Systems
Vector & Graph Databases
Engineering Leadership
Workflow Orchestration
Llms, Rag, Generative Ai
Cloud Infrastructure (Gcp/Aws)
Model Governance
Team Mentoring & Strategy
Kubernetes & Containerization
Cost Optimization
Terraform & Iac
Mlops & Ci/Cd Pipelines
Python, Go (Learning)
Observability & Monitoring
Cloud Platforms: Aws (Sagemaker, Ec2, Lambda, S3, Dynamodb, Redshift, Step Functions)
Gcp-Ready: Vertex Ai (Training, Pipelines, Model Registry, Feature Store), Gke, Cloud Run, Bigquery, Dataflow, Cloud Storage, Iam
Ml & Ai: Tensorflow, Pytorch, Scikit-Learn, Xgboost, Llms (Gpt, Claude), Rag Systems, Langchain, Langgraph, Agentic Ai (Mcp), Computer Vision (Opencv), Nlp, Generative Ai, Model Governance
Orchestration & Workflow: Metaflow, Argo Workflows, Airflow, Kubeflow (Vertex Pipelines-Compatible), Aws Step Functions
Infrastructure & Devops: Kubernetes, Docker, Terraform, Helm Charts, Spinnaker, Gitops, Ci/Cd (Github Actions, Gitlab Ci), Infrastructure-As-Code
Databases: Postgresql, Vector Dbs (Pgvector, Pinecone-Ready), Graph Dbs (Neo4j), Redis, Mongodb, Snowflake, Bigquery, Dynamodb
Observability: Prometheus, Grafana, Cloudwatch, Logging, Alerting, Model Monitoring, Performance Tracking, Slo/Sla Management
Programming: Python (Expert), Typescript, C, Go (Learning), Sql
Distributed Systems: Distributed Training, Data Pipelines, Microservices, Event-Driven Architecture, Scalability Patterns
Ml Governance: Model Lineage, Versioning, A/B Testing, Feature Engineering, Experiment Tracking, Reproducibility, Audit Trails

Languages

English

Advanced

German

Intermediate

Education

Oct 2010 - Sep 2013

Kiel University

Master of Science in Digital Communication · Digital Communication · Kiel, Germany

Jan 2006 - Jun 2010

Ganpat University

Bachelor's Degree in Electronics and Communications Engineering · Electronics and Communications Engineering · India

Statistics

Experience

Total positions 5

Experience in Banking and Finance 4.5 y

Avg length 1 y 9 m

Longest experience 3 y 7 m

Global Experience

Countries worked in 1 (Germany)

Primary country Germany

Expertise

Recent roles Lead ML Platform Engineer, Lead Machine Learning Engineer, Senior Machine Learning Engineer

Main industries Banking and Finance, Information Technology, Automotive

Main business areas Information Technology, Product Development, Business Intelligence

Qualifications

Highest degree Master

Profile

Created

June 2026

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Frequently asked questions

Have questions? Find more information here.

Where is Deepak based?

Deepak is based in Berlin, Germany.

What languages does Deepak speak?

Deepak speaks the following languages: English (Advanced), German (Intermediate).

How many years of experience does Deepak have?

Deepak has at least 9 years of experience. During this time, Deepak has worked in at least 4 different roles and for 5 different companies. The average length of individual experience is 2 years and 10 months. Note that Deepak may not have shared all experience and actually has more experience.

What roles would Deepak be best suited for?

Based on recent experience, Deepak would be well-suited for roles such as: Lead ML Platform Engineer, Lead Machine Learning Engineer, Senior Machine Learning Engineer.

What is Deepak's latest experience?

Deepak's most recent position is Lead ML Platform Engineer at Billie GmbH.

What companies has Deepak worked for in recent years?

In recent years, Deepak has worked for Billie GmbH, TwoTronic GmbH, Latana GmbH, and Candis GmbH.

Which industries is Deepak most experienced in?

Deepak is most experienced in industries like Banking and Finance, Information Technology, and Fashion. Deepak also has some experience in Retail and Automotive.

Which business areas is Deepak most experienced in?

Deepak is most experienced in business areas like Information Technology, Product Development, and Business Intelligence. Deepak also has some experience in Project Management.

Which industries has Deepak worked in recently?

Deepak has recently worked in industries like Banking and Finance, Information Technology, and Automotive.

Which business areas has Deepak worked in recently?

Deepak has recently worked in business areas like Information Technology, Product Development, and Business Intelligence.

What is Deepak's education?

Deepak holds a Master in Digital Communication from Kiel University and a Bachelor in Electronics and Communications Engineering from Ganpat University.

What is the availability of Deepak?

Deepak is immediately available full-time for suitable projects.

What is the rate of Deepak?

Deepak's rate depends on the specific project requirements. Please use the Meet button on the profile to schedule a meeting and discuss the details.